Multi-parameter prediction of acute cardiac episodes and attacks

ABSTRACT

In some examples, processing circuitry of a medical device system determines, for each of a plurality of patient parameters, a difference metric for a current period based on a value of a patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period, and determines a score for the current period based on a sum of the difference metrics for at least some of the plurality of patient parameters. The processing circuitry determines a threshold for the current period based on scores determined for N periods that precede the current period, compares the score for the current period to the threshold, and determines whether to generate an alert indicating that an acute cardiac event of the patient, e.g., ventricular tachyarrhythmia, is predicted, and/or deliver a therapy configured to prevent the acute cardiac event, based on the comparison.

This application claims the benefit of U.S. Provisional Application No.62/349,504, filed Jun. 13, 2016, the entire content of which isincorporated herein by reference.

TECHNICAL FIELD

The disclosure relates generally to medical device systems and, moreparticularly, medical device systems configured to monitor patientparameters, assess risks relevant to cardiac status, predict theimpending occurrence of a cardiac event, and initiate measure(s) thatprevents the cardiac event from occurring.

BACKGROUND

Implantable medical devices (IMDs) and external medical devices (e.g.,wearable devices, insertable cardiac monitors, implantable pacemakers,or implantable cardioverter-defibrillators) may record cardiacelectrogram (EGM) signals for sensing cardiac events such as P-waves andR-waves. IMDs may detect episodes of bradycardia, tachycardia, orfibrillation from the sensed cardiac events, and respond to the episodesas needed with pacing therapy or high-voltage anti-tachyarrhythmiashocks (e.g., cardioversion or defibrillation shocks). Some IMDsinclude, or are or part of a system that includes, sensors that generateother physiological signals, such as signals that vary based on patientmovement or activity, cardiovascular pressure, blood oxygen saturation,edema, or thoracic impedance. Physiological parameters determined basedon such signals may be used to assist in the detection of arrhythmia, aswell as the detection or monitoring of other cardiac conditions, such asheart failure or infarction. Delivery of therapy in response todetection of a cardiac event, such as ventricular tachyarrhythmia, maynegatively impact a patient's quality of life, while delayed treatmentmay present risk to the patient.

SUMMARY

In general, this disclosure is directed to systems and techniques forpredicting the occurrence of an acute cardiac event, episode, or attack(referred to herein as “cardiac events”), such as a ventriculartachyarrhythmia episode, heart failure decompensation, or ischemia. Thesystems and techniques include determining a respective value for eachof a plurality of parameters of a patient (e.g., physiological orpathophysiological) during each of a plurality of periods, which may beat least one hour, such as approximately one day. In some examples,processing circuitry of a medical device system indicates that the acutecardiac event is predicted if the cumulative degree of change across thephysiological parameters during the current period is significantlygreater than the variation in the physiological parameters during Nrecently preceding periods. In some examples, the processing circuitrymay responsively provide an alert indicating that the acute cardiacevent is predicted and/or deliver a therapy configured to prevent thepredicted cardiac event.

In some examples, processing circuitry of a medical device systemdetermines, for each of a plurality of patient parameters, a differencemetric for a current period based on a value of a patient parameterdetermined for the current period and a value of the patient parameterdetermined for an immediately preceding period. In some examples, theprocessing circuitry determines a score for the current period based ona sum of the respective difference metrics for the plurality of patientparameters for the current period for at least some of the plurality ofpatient parameters. The processing circuitry determines a threshold forthe current period based on scores determined for N periods that precedethe current period, and compares the score for the current period to thethreshold for the current period.

IMDs, such as implantable cardioverter-defibrillators (ICDs), aregenerally able to effectively detect and terminate tachyarrhythmias.However, even when properly detected and terminated, tachyarrhythmiasand anti-tachyarrhythmia shocks may negatively impact a patient, and theshocks may negatively impact the longevity of the IMD. The techniques ofthis disclosure may avoid such negative impacts by enabling accurateprediction of tachyarrhythmia, and other acute cardiac events, prior totheir occurrence. In some examples, the techniques of this disclosuremay enable a medical device or clinician to provide a treatment to thepatient that may prevent the occurrence of a predicted cardiac event.For example, a patient may receive a warning from implanted/wearabledevice and can consult with a clinician. In some examples, the medicaldevice can automatically initiate a preventive measure targeting thepredicted event in response to the prediction.

In an example, a medical device system comprises sensing circuitryconfigured to generate one or more physiological signals of a patient,and processing circuitry. For each of a plurality of periods, theprocessing circuitry is configured to determine a respective value foreach of a plurality of patient parameters, wherein, for one or more ofthe plurality of patient parameters, the respective values aredetermined based on the one or more physiological signals generatedduring the period, for each of the plurality of patient parameters,determine a difference metric for a current period for each of theplurality of periods based on a value of the patient parameterdetermined for the current period and a value of the patient parameterdetermined for an immediately preceding period of the plurality periods,determine a score for the current period based on a sum of thedifference metrics for the current period for the one or more of theplurality of patient parameters, determine a threshold for the currentperiod based on scores determined for N periods of the plurality ofperiods that precede the current period, wherein N is an integerconstant, compare the score for the current period to the threshold forthe current period, and determine whether to generate an alertindicating that an acute cardiac event of the patient is predicted basedon the comparison.

In another example, a method comprises generating, by sensing circuitryof a medical device system, one or more physiological signals of apatient. The method further comprises, for each of a plurality ofperiods, by processing circuitry of the medical device system,determining a respective value for each of a plurality of patientparameters, wherein, for one or more of the plurality of patientparameters, the respective values are determined based on the one ormore physiological signals generated during the period, for each of theplurality of patient parameters, determining a difference metric for acurrent period for each of the plurality of periods based on a value ofthe patient parameter determined for the current period and a value ofthe patient parameter determined for an immediately preceding period ofthe plurality periods, determining a score for the current period basedon a sum of the difference metrics for the current period for the one ormore of the plurality of patient parameters, determining a threshold forthe current period based on scores determined for N periods of theplurality of periods that precede the current period, wherein N is aninteger constant, comparing the score for the current period to thethreshold for the current period, and determining whether to generate analert indicating that an acute cardiac event of the patient is predictedbased on the comparison.

In another example, a medical device system comprises means forgenerating one or more physiological signals of a patient, and for eachof a plurality of periods, means for determining a respective value foreach of a plurality of patient parameters, wherein, for one or more ofthe plurality of patient parameters, the respective values aredetermined based on the one or more physiological signals generatedduring the period, for each of the plurality of patient parameters,means for determining a difference metric for a current period for eachof the plurality of periods based on a value of the patient parameterdetermined for the current period and a value of the patient parameterdetermined for an immediately preceding period of the plurality periods,means for determining a score for the current period based on a sum ofthe difference metrics for the current period for the one or more of theplurality of patient parameters, means for determining a threshold forthe current period based on scores determined for N periods of theplurality of periods that precede the current period, wherein N is aninteger constant, means for comparing the score for the current periodto the threshold for the current period, and means for determiningwhether to generate an alert indicating that an acute cardiac event ofthe patient is predicted based on the comparison.

In another example, a non-transitory computer-readable storage mediumcomprises instructions, that when executed by processing circuitry of amedical device system, cause the medical device system to receive one ormore physiological signals of a patient, and for each of a plurality ofperiods, determine a respective value for each of a plurality of patientparameters, wherein, for one or more of the plurality of patientparameters, the respective values are determined based on the one ormore physiological signals generated during the period, for each of theplurality of patient parameters, determine a difference metric for acurrent period for each of the plurality of periods based on a value ofthe patient parameter determined for the current period and a value ofthe patient parameter determined for an immediately preceding period ofthe plurality periods, determine a score for the current period based ona sum of the difference metrics for the current period for the one ormore of the plurality of patient parameters, determine a threshold forthe current period based on scores determined for N periods of theplurality of periods that precede the current period, wherein N is aninteger constant, compare the score for the current period to thethreshold for the current period, and determine whether to generate analert indicating that an acute cardiac event of the patient is predictedbased on the comparison.

This summary is intended to provide an overview of the subject matterdescribed in this disclosure. It is not intended to provide an exclusiveor exhaustive explanation of the apparatus and methods described indetail within the accompanying drawings and description below. Thedetails of one or more aspects of the disclosure are set forth in theaccompanying drawings and the description below.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual drawing illustrating an example medical devicesystem in conjunction with a patient.

FIG. 2 is a conceptual drawing illustrating another example medicaldevice system in conjunction with a patient.

FIG. 3 is a perspective drawing illustrating an example configuration ofthe implantable cardiac monitor of FIG. 2.

FIGS. 4A-4C are a front-view, side-view, and top-view conceptualdrawings, respectively, illustrating another example medical devicesystem in conjunction with a patient.

FIG. 5 is a conceptual drawing illustrating another example medicaldevice system in conjunction with a patient.

FIG. 6 is a conceptual diagram illustrating an example configuration ofthe intracardiac pacing device of FIGS. 4A-5.

FIG. 7 is a functional block diagram illustrating an exampleconfiguration of an implantable medical device.

FIG. 8 is a functional block diagram illustrating an exampleconfiguration of an external device configured to communicate with oneor more implantable medical devices.

FIG. 9 is a functional block diagram illustrating an example system thatincludes remote computing devices, such as a server and one or moreother computing devices, that are connected to an implantable medicaldevice and/or external device via a network.

FIG. 10 is a timing diagram illustrating values of a physiologicalparameter of a patient over a plurality of time periods.

FIG. 11 is a tabular representation of an example technique forperiodically determining a score based on respective difference metricsfor each of a plurality of physiological parameters.

FIG. 12 is a tabular representation of another example technique forperiodically determining a score based on respective difference metricsfor each of a plurality of physiological parameters.

FIGS. 13A and 13B are timing diagrams illustrating example techniquesfor determining a window of N preceding periods.

FIG. 14 is a flow diagram illustrating an example technique that may beimplemented by a medical device system to provide an alert and/orpreventative measure(s) in response to an acute cardiac event beingpredicted.

FIG. 15 is a flow diagram illustrating an example technique that may beimplemented by a medical device system to determine a score based on aplurality of difference metrics associated with respective physiologicalparameters.

FIG. 16 is a flow diagram illustrating an example technique that may beimplemented by a medical device system to select one or morepreventative measure(s) for delivery in response to an acute cardiacevent being predicted.

FIG. 17 is a flow diagram illustrating an example technique that may beimplemented by a medical device system to modify a set of patientparameters or weightings applied to patient parameters used to determinewhether an acute cardiac event is predicted.

FIGS. 18-22 are tables of experimental results illustrating theperformance of example techniques of this disclosure in predictingventricular tachyarrhythmia.

FIG. 23 is a table illustrating a receiver operator characteristic for acoefficient used to determine a threshold for determining whether anacute cardiac event is predicted according to the example techniques ofthis disclosure.

FIG. 24 is a conceptual diagram illustrating patient parameters, e.g.,physiological and pathophysiological parameters, that may contribute tothe occurrence of an acute cardiac event.

DETAILED DESCRIPTION

In general, this disclosure describes example techniques related topredicting an acute occurrence of a cardiac event or attack (may bereferred to herein as “acute cardiac event”), such as a ventriculartachyarrhythmia, heart failure decompensation, and ischemia, andresponsively providing an alert indicating that the acute cardiac eventis predicted, and/or deliver a therapy configured to prevent thepredicted cardiac event. In the following description, references aremade to illustrative examples. It is understood that other examples maybe utilized without departing from the scope of the disclosure.

FIG. 1 is a conceptual drawing illustrating an example medical devicesystem 8A in conjunction with a patient 14A. Medical device system 8A isan example of a medical device system configured to implement thetechniques described herein for predicting the acute occurrence of acardiac event, such as a ventricular tachyarrhythmia, and responsivelyproviding an alert indicating that the acute cardiac event is predicted,and/or delivering a therapy configured to prevent the predicted cardiacevent. In the illustrated example, medical device system 8A includes animplantable medical device (IMD) 10A coupled to a ventricular lead 20and an atrial lead 21. IMD 10A may be an ICD capable of deliveringpacing, cardioversion and defibrillation therapy to the heart 16A of apatient 14A, and will be referred to as ICD 10A hereafter.

Ventricular lead 20 and atrial lead 21 are electrically coupled to ICD10A and extend into the patient's heart 16A. Ventricular lead 20includes electrodes 22 and 24 shown positioned on the lead in thepatient's right ventricle (RV) for sensing ventricular EGM signals andpacing in the RV. Atrial lead 21 includes electrodes 26 and 28positioned on the lead in the patient's right atrium (RA) for sensingatrial EGM signals and pacing in the RA.

Ventricular lead 20 additionally carries a high voltage coil electrode42, and atrial lead 21 carries a high voltage coil electrode 44, used todeliver cardioversion and defibrillation shocks. The term“anti-tachyarrhythmia shock” may be used herein to refer to bothcardioversion shocks and defibrillation shocks. In other examples,ventricular lead 20 may carry both of high voltage coil electrodes 42and 44, or may carry a high voltage coil electrode in addition to thoseillustrated in the example of FIG. 1.

ICD 10A may use both ventricular lead 20 and atrial lead 21 to acquirecardiac electrogram (EGM) signals from patient 14A and to delivertherapy in response to the acquired data. Medical device system 8A isshown as having a dual chamber ICD configuration, but other examples mayinclude one or more additional leads, such as a coronary sinus leadextending into the right atrium, through the coronary sinus and into acardiac vein to position electrodes along the left ventricle (LV) forsensing LV EGM signals and delivering pacing pulses to the LV. In otherexamples, a medical device system may be a single chamber system, orotherwise not include atrial lead 21.

Processing circuitry, sensing circuitry, and other circuitry configuredfor performing the techniques described herein are housed within asealed housing 12. Housing 12 (or a portion thereof) may be conductiveso as to serve as an electrode for pacing or sensing or as an activeelectrode during defibrillation. As such, housing 12 is also referred toherein as “housing electrode” 12.

ICD 10A may transmit EGM signal data and cardiac rhythm episode dataacquired by ICD 10A, as well as data regarding delivery of therapy byICD 10A, to an external device 30A. External device 30A may be acomputing device that may be used in a home, ambulatory setting, clinic,or hospital setting, to communicate with ICD 10A via wireless telemetry.External device 30A may be coupled to a remote patient monitoringsystem, such as Carelink®, available from Medtronic plc, of Dublin,Ireland. External device 30A may be, as examples, a programmer, externalmonitor, or consumer device, e.g., smart phone.

External device 30A may be used to program commands or operatingparameters into ICD 10A for controlling its functioning, e.g., whenconfigured as a programmer for ICD 10A. External device 30A may be usedto interrogate ICD 10A to retrieve data, including device operationaldata as well as physiological data accumulated in IMD memory. Theinterrogation may be automatic, e.g., according to a schedule, or inresponse to a remote or local user command. Programmers, externalmonitors, and consumer devices are examples of external devices 30A thatmay be used to interrogate ICD 10A. Examples of communication techniquesused by ICD 10A and external device 30A include radiofrequency (RF)telemetry, which may be an RF link established via Bluetooth, WiFi, ormedical implant communication service (MICS).

In some examples, as illustrated in FIG. 1, medical device system 8A mayalso include a pressure-sensing IMD 50. In the illustrated example,pressure-sensing IMD 50 is implanted in the pulmonary artery of patient14A. In some examples, one or more pressure-sensing IMDs 50 mayadditionally or alternatively be implanted within a chamber of heart16A, or generally at other locations in the circulatory system.

In one example, pressure-sensing IMD 50 is configured to sense bloodpressure of patient 14A. For example, pressure-sensing IMD 50 may bearranged in the pulmonary artery and be configured to sense the pressureof blood flowing from the right ventricle outflow tract (RVOT) from theright ventricle through the pulmonary valve to the pulmonary artery.Pressure-sensing IMD 50 may therefore directly measure the pulmonaryartery diastolic pressure (PAD) of patient 14A. The PAD value is apressure value that can be employed in patient monitoring. For example,PAD may be used as a basis for evaluating congestive heart failure in apatient.

In other examples, however, pressure-sensing IMD 50 may be employed tomeasure blood pressure values other than PAD. For example,pressure-sensing IMD 50 may be arranged in right ventricle 28 of heart14 to sense RV systolic or diastolic pressure, or may sense systolic ordiastolic pressures at other locations of the cardiovascular system,such as within the pulmonary artery. As shown in FIG. 1,pressure-sensing IMD 50 is positioned in the main trunk of pulmonaryartery 39. In other examples, a sensor, such as pressure-sensing IMD 50may be either positioned in the right or left pulmonary artery beyondthe bifurcation of the pulmonary artery.

Moreover, the placement of pressure-sensing IMD 50 is not restrictednecessarily to the pulmonary side of the circulation. Pressure-sensingIMD 50 could potentially be placed in the systemic side of thecirculation. For example, under certain conditions and with appropriatesafety measures, pressure-sensing IMD 50 could even be placed in theleft atrium, left ventricle, or aorta. Additionally, pressure-sensingIMD 50 is not restricted to placement within the cardiovascular system.For example, the pressure-sensing IMD 50 might be placed in the renalcirculation. Placement of pressure-sensing IMD 50 in the renalcirculation may be beneficial, for example, to monitor the degree ofrenal insufficiency in the patient based on the monitoring of pressureor some other indication of renal circulation by pressure-sensing IMD50.

In some examples, pressure-sensing IMD 50 includes a pressure sensorconfigured to respond to the absolute pressure inside the pulmonaryartery of patient 14A. Pressure-sensing IMD 50 may be, in such examples,any of a number of different types of pressure sensors. One form ofpressure sensor that may be useful for measuring blood pressure is acapacitive pressure sensor. Another example pressure sensor is aninductive sensor. In some examples, pressure-sensing IMD 50 may alsocomprise a piezoelectric or piezoresistive pressure transducer. In someexamples, pressure-sensing IMD 50 may comprise a flow sensor.

In one example, pressure-sensing IMD 50 comprises a leadless pressuresensor including capacitive pressure sensing elements configured tomeasure blood pressure within the pulmonary artery. Pressure-sensing IMD50 may be in wireless communication with ICD 10A and/or external device30A, e.g., in order to transmit blood pressure measurements to one orboth of the devices. Pressure-sensing IMD 50 may employ, e.g., radiofrequency (RF) or other telemetry techniques for communicating with ICD10A and other devices, including, e.g., external device 30A. In anotherexample, pressure-sensing IMD 50 may include a tissue conductancecommunication (TCC) system by which the device employs tissue of patient14A as an electrical communication medium over which to send and receiveinformation to and from ICD 10A and/or external device 30A.

Medical device system 8A is an example of a medical device systemconfigured to determine whether an acute occurrence of a cardiac event,such as a ventricular tachyarrhythmia, is predicted to occur, and toresponsively provide an alert indicating that the acute cardiac event ispredicted, and/or deliver a therapy configured to prevent the predictedcardiac event. The techniques may be performed by processing circuitryof medical device system 8A, such as processing circuitry of one or bothof ICD 10A and external device 30A, individually, or collectively.

The techniques include determining a respective value for each of aplurality of parameters of a patient, e.g., physiological and/orpathophysiological, during each of a plurality of periods, which may beat least one hour, such as between approximately one day andapproximately three days, e.g., in one example, approximately one day.The processing circuitry may determine the values of at least some thepatient parameters based on physiological signals generated by sensingcircuitry of one or both of ICD 10A and pressure-sensing IMD 50, such asa cardiac EGM signal generated by sensing circuitry of ICD 10A, or apulmonary artery or other cardiovascular pressure signal generated bypressure-sensing IMD 50. In some examples, one or both of ICD 10A andpressure-sensing IMD 50 may include or be coupled to one or more othersensors that generate one or more other physiological signals, such assignals that vary based on patient motion and/or posture, blood flow,respiration, or edema. The processing circuitry may determine otherpatient parameters based on therapy delivered by ICD 10A, such aspatient parameters indicating the extent to which patient 14A isdependent on pacing, e.g., a percentage of time or othercharacterization of amount of pacing delivered to the patient.

In some examples, the processing circuitry of medical device system 8Aindicates that the acute cardiac event is predicted if the cumulativedegree of change across the patient parameters during the current periodis significantly greater than the variation in the patient parametersduring N recently preceding periods. For example, as will be describedin greater detail below, the processing circuitry may determine, foreach of a plurality of patient parameters, a difference metric for acurrent period based on a value of a patient parameter determined forthe current period and a value of the patient parameter determined foran immediately preceding period. In some examples, the processingcircuitry determines a score for the current period based on a sum ofthe difference metrics for the current period for at least some of theplurality of patient parameters. The processing circuitry determines athreshold for the current period based on scores determined for Nperiods that precede the current period, and compares the score for thecurrent period to the threshold for the current period to determinewhether the acute event is predicted. If the processing circuitrydetermines that the acute cardiac event is predicted, the processingcircuitry may generate an alert and, in some examples, control deliveryof one or more preventative measures configured to prevent the event,such as cardiac pacing, neuromodulation, or one or more therapeuticsubstances, e.g., drugs.

Medical device system 8A is one example of a medical device system thatmay be configured to implement the techniques described herein fordetermining whether an acute cardiac event is predicted. Other examplemedical device systems that may be configured to implement thetechniques are described with respect to FIGS. 2-6. Although describedherein primarily in the context of implantable medical devicesgenerating physiological signals and, in some examples, deliveringtherapy, a medical device system that implements the techniquesdescribed in this disclosure may additionally or alternatively includean external medical device, e.g., external cardiac monitor, and/orexternal pacemaker, cardioverter and/or defibrillator, configured togenerate one or more of the physiological signals described herein,determine whether an acute cardiac event is predicted, provide an alert,and/or deliver one or more of the preventative therapies describedherein.

FIG. 2 is a conceptual drawing illustrating another example medicaldevice system 8B in conjunction with a patient 14B. Medical devicesystem 8B is another example of a medical device system configured toimplement the techniques described herein for predicting the acuteoccurrence of a cardiac event, such as a ventricular tachyarrhythmia,and responsively providing an alert indicating that the acute cardiacevent is predicted. In the illustrated example, medical device system 8Bincludes an IMD 10B and an external device 30B.

IMD 10B is an insertable cardiac monitor (ICM) capable of sensing andrecording cardiac EGM signals from a position outside of heart 16B, andwill be referred to as ICM 10B hereafter. In some examples, ICM 10Bincludes or is coupled to one or more additional sensors that generateone or more other physiological signals, such as signals that vary basedon patient motion and/or posture, blood flow, or respiration. ICM 10Bmay be implanted outside of the thorax of patient 14B, e.g.,subcutaneously or submuscularly, such as the pectoral locationillustrated in FIG. 2. In some examples, ICM 10B may take the form of aReveal LINQ™ ICM, available from Medtronic plc, of Dublin, Ireland.

External device 30B may be configured in a manner substantially similarto that described above with respect to external device 30A and FIG. 1.External device 30B may wirelessly communicate with ICM 10B, e.g., toprogram the functionality of the ICM, and to retrieve recordedphysiological signals and/or patient parameter values or other dataderived from such signals from the ICM. Both ICM 10B and external device30B include processing circuitry, and the processing circuitry of eitheror both device may perform the techniques described herein, such asdetermining patient parameter values for a period, determiningdifference metrics based on the patient parameter values, determining ascore for the period based on the difference metrics, and comparing thescore to a determined threshold.

Based on the comparison, the processing circuitry may also be configuredto provide an alert to a user, e.g., clinician or patient 14B, that theacute cardiac event is predicted, e.g., via external device 30B.Although ICM 10B is not described as being configured to delivertherapy, patient 14B, a clinician, or another implanted or externalmedical device may deliver or take a preventative measure to prevent theacute cardiac event predicted by medical device system 8B. Ventriculartachyarrhythmia is one example of an acute cardiac event that may bepredicted according to the techniques of this disclosure. Other exampleacute cardiac events include heart failure decompensation and myocardialinfarction.

Although not illustrated in the example of FIG. 2, a medical devicesystem configured to implement the techniques of this disclosure mayinclude one or more implanted or external medical devices in addition toor instead of ICM 10B. For example, a medical device system may includea pressure sensing IMD 50, vascular ICD (e.g., ICD 10A of FIG. 1),extravascular ICD (e.g., ICD 10C of FIGS. 4A-5), or cardiac pacemaker(e.g., IPD 10D of FIGS. 4A-6 or a cardiac pacemaker implanted outsidethe heart but coupled to intracardiac or epicardial leads). One or moresuch devices may generate physiological signals, and include processingcircuitry configured to perform, in whole or in part, the techniquesdescribed herein for predicting an acute cardiac event. The implanteddevices may communicate with each other and/or an external device 30,and one of the implanted or external devices may ultimately determinewhether the acute cardiac event is predicted based on informationreceived from the other device(s).

FIG. 3 is a conceptual drawing illustrating an example configuration ofICM 10B. In the example shown in FIG. 4, ICM 300 may be embodied as amonitoring device having housing 62, proximal electrode 64 and distalelectrode 66. Housing 62 may further comprise first major surface 68,second major surface 70, proximal end 72, and distal end 74. Housing 62encloses electronic circuitry located inside the ICM 10B and protectsthe circuitry contained therein from body fluids. Electricalfeedthroughs provide electrical connection of electrodes 64 and 66.

In the example shown in FIG. 3, ICM 10B is defined by a length L, awidth W and thickness or depth D and is in the form of an elongatedrectangular prism wherein the length L is much larger than the width W,which in turn is larger than the depth D. In one example, the geometryof the ICM 10B—in particular a width W greater than the depth D—isselected to allow ICM 10B to be inserted under the skin of the patientusing a minimally invasive procedure and to remain in the desiredorientation during insertion. For example, the device shown in FIG. 3includes radial asymmetries (notably, the rectangular shape) along thelongitudinal axis that maintains the device in the proper orientationfollowing insertion. For example, in one example the spacing betweenproximal electrode 64 and distal electrode 66 may range from 30millimeters (mm) to 55 mm, 35 mm to 55 mm, and from 40 mm to 55 mm andmay be any range or individual spacing from 25 mm to 60 mm. In addition,ICM 10B may have a length L that ranges from 30 mm to about 70 mm. Inother examples, the length L may range from 40 mm to 60 mm, 45 mm to 60mm and may be any length or range of lengths between about 30 mm andabout 70 mm. In addition, the width W of major surface 68 may range from3 mm to 10 mm and may be any single or range of widths between 3 mm and10 mm. The thickness of depth D of ICM 10B may range from 2 mm to 9 mm.In other examples, the depth D of ICM 10B may range from 2 mm to 5 mmand may be any single or range of depths from 2 mm to 9 mm. In addition,ICM 10B according to an example of the present disclosure is has ageometry and size designed for ease of implant and patient comfort.Examples of ICM 10B described in this disclosure may have a volume ofthree cubic centimeters (cm) or less, 1.5 cubic cm or less or any volumebetween three and 1.5 cubic centimeters.

In the example shown in FIG. 3, once inserted within the patient, thefirst major surface 68 faces outward, toward the skin of the patientwhile the second major surface 70 is located opposite the first majorsurface 68. In addition, in the example shown in FIG. 3, proximal end 72and distal end 74 are rounded to reduce discomfort and irritation tosurrounding tissue once inserted under the skin of the patient. ICM 10B,including instrument and method for inserting ICM 10B is described, forexample, in U.S. Patent Publication No. 2014/0276928, incorporatedherein by reference in its entirety.

Proximal electrode 64 and distal electrode 66 are used to sense cardiacsignals, e.g. ECG signals, intra-thoracically or extra-thoracically,which may be sub-muscularly or subcutaneously. ECG signals may be storedin a memory of the ICM 10B, and ECG data may be transmitted viaintegrated antenna 82 to another medical device, which may be anotherimplantable device or an external device, such as external device 30B.In some example, electrodes 64 and 66 may additionally or alternativelybe used for sensing any bio-potential signal of interest, which may be,for example, an EGM, EEG, EMG, or a nerve signal, from any implantedlocation.

In the example shown in FIG. 3, proximal electrode 64 is in closeproximity to the proximal end 72 and distal electrode 66 is in closeproximity to distal end 74. In this example, distal electrode 66 is notlimited to a flattened, outward facing surface, but may extend fromfirst major surface 68 around rounded edges 76 and/or end surface 78 andonto the second major surface 70 so that the electrode 66 has athree-dimensional curved configuration. In the example shown in FIG. 3,proximal electrode 64 is located on first major surface 68 and issubstantially flat, outward facing. However, in other examples proximalelectrode 64 may utilize the three dimensional curved configuration ofdistal electrode 66, providing a three dimensional proximal electrode(not shown in this example). Similarly, in other examples distalelectrode 66 may utilize a substantially flat, outward facing electrodelocated on first major surface 68 similar to that shown with respect toproximal electrode 64. The various electrode configurations allow forconfigurations in which proximal electrode 64 and distal electrode 66are located on both first major surface 68 and second major surface 70.In other configurations, such as that shown in FIG. 3, only one ofproximal electrode 64 and distal electrode 66 is located on both majorsurfaces 68 and 70, and in still other configurations both proximalelectrode 64 and distal electrode 66 are located on one of the firstmajor surface 68 or the second major surface 70 (i.e., proximalelectrode 64 located on first major surface 68 while distal electrode 66is located on second major surface 70). In another example, ICM 10B mayinclude electrodes on both major surface 68 and 70 at or near theproximal and distal ends of the device, such that a total of fourelectrodes are included on ICM 10B. Electrodes 64 and 66 may be formedof a plurality of different types of biocompatible conductive material,e.g. stainless steel, titanium, platinum, iridium, or alloys thereof,and may utilize one or more coatings such as titanium nitride or fractaltitanium nitride.

In the example shown in FIG. 3, proximal end 72 includes a headerassembly 80 that includes one or more of proximal electrode 64,integrated antenna 82, anti-migration projections 84, and/or suture hole86. Integrated antenna 82 is located on the same major surface (i.e.,first major surface 68) as proximal electrode 64 and is also included aspart of header assembly 80. Integrated antenna 82 allows ICM 10B totransmit and/or receive data. In other examples, integrated antenna 82may be formed on the opposite major surface as proximal electrode 64, ormay be incorporated within the housing 82 of ICM 10B. In the exampleshown in FIG. 3, anti-migration projections 84 are located adjacent tointegrated antenna 82 and protrude away from first major surface 68 toprevent longitudinal movement of the device. In the example shown inFIG. 3, anti-migration projections 84 includes a plurality (e.g., nine)small bumps or protrusions extending away from first major surface 68.As discussed above, in other examples anti-migration projections 84 maybe located on the opposite major surface as proximal electrode 64 and/orintegrated antenna 82. In addition, in the example shown in FIG. 3header assembly 80 includes suture hole 86, which provides another meansof securing ICM 10B to the patient to prevent movement following insert.In the example shown, suture hole 86 is located adjacent to proximalelectrode 64. In one example, header assembly 80 is a molded headerassembly made from a polymeric or plastic material, which may beintegrated or separable from the main portion of ICM 10B.

FIGS. 4A-4C are front-view, side-view, and top-view conceptual drawings,respectively, illustrating another example medical device system 8C inconjunction with a patient 14C. Medical device system 8C is anotherexample of a medical device system configured to implement thetechniques described herein for predicting the acute occurrence of acardiac event, such as a ventricular tachyarrhythmia, and responsivelyproviding an alert indicating that the acute cardiac event is predicted.

In the illustrated example, medical device system 8C includes anextracardiovascular ICD system 100A implanted within a patient 14C. ICDsystem 100A includes an IMD 10C, which is an ICD and is referred tohereafter as ICD 10C, connected to at least one implantable cardiacdefibrillation lead 102A. ICD 10C is configured to deliver high-energycardioversion or defibrillation pulses to a patient's heart 16C whenatrial or ventricular fibrillation is detected. Cardioversion shocks aretypically delivered in synchrony with a detected R-wave whenfibrillation detection criteria are met. Defibrillation shocks aretypically delivered when fibrillation criteria are met, and the R-wavecannot be discerned from signals sensed by ICD 10C.

ICD 10C is implanted subcutaneously or submuscularly on the left side ofpatient 14C above the ribcage. Defibrillation lead 102A may be implantedat least partially in a substernal location, e.g., between the ribcageand/or sternum 110 and heart 16C. In one such configuration, a proximalportion of lead 102A extends subcutaneously from ICD 10C toward sternum110 and a distal portion of lead 102A extends superior under or belowthe sternum 110 in the anterior mediastinum 112 (FIG. 4C). The anteriormediastinum 112 is bounded laterally by the pleurae 116 (FIG. 1C),posteriorly by the pericardium 114 (FIG. 4C), and anteriorly by thesternum 110. In some instances, the anterior wall of the anteriormediastinum may also be formed by the transversus thoracis and one ormore costal cartilages. The anterior mediastinum includes a quantity ofloose connective tissue (such as areolar tissue), some lymph vessels,lymph glands, substernal musculature (e.g., transverse thoracic muscle),branches of the internal thoracic artery, and the internal thoracicvein. In one example, the distal portion of lead 102A extends along theposterior side of the sternum 110 substantially within the looseconnective tissue and/or substernal musculature of the anteriormediastinum. Lead 102A may be at least partially implanted in otherintrathoracic locations, e.g., other non-vascular, extra-pericardiallocations, including the gap, tissue, or other anatomical featuresaround the perimeter of and adjacent to, but not attached to, thepericardium or other portion of the heart and not above the sternum 110or ribcage.

In other examples, lead 102A may be implanted at otherextracardiovascular locations. For example, defibrillation lead 102A mayextend subcutaneously above the ribcage from ICD 10C toward a center ofthe torso of patient 14C, bend or turn near the center of the torso, andextend subcutaneously superior above the ribcage and/or sternum 110.Defibrillation lead 102A may be offset laterally to the left or theright of the sternum 110 or located over the sternum 110. Defibrillationlead 102A may extend substantially parallel to the sternum 110 or beangled lateral from the sternum 110 at either the proximal or distalend.

Defibrillation lead 102A includes an insulative lead body having aproximal end that includes a connector 104 configured to be connected toICD 10C and a distal portion that includes one or more electrodes.Defibrillation lead 102A also includes one or more conductors that forman electrically conductive path within the lead body and interconnectthe electrical connector and respective ones of the electrodes.

Defibrillation lead 102A includes a defibrillation electrode thatincludes two sections or segments 106A and 106B, collectively (oralternatively) defibrillation electrode 106. The defibrillationelectrode 106 is toward the distal portion of defibrillation lead 102A,e.g., toward the portion of defibrillation lead 102A extending along thesternum 110. Defibrillation lead 102A is placed below and/or alongsternum 110 such that a therapy vector between defibrillation electrodes106A or 106B and a housing electrode formed by or on ICD 10C (or othersecond electrode of the therapy vector) is substantially across aventricle of heart 16C. The therapy vector may, in one example, beviewed as a line that extends from a point on defibrillation electrode106 (e.g., a center of one of the defibrillation electrode sections 106Aor 106B) to a point on the housing electrode of ICD 10C. Defibrillationelectrode 106 may, in one example, be an elongated coil electrode.

Defibrillation lead 102A may also include one or more sensingelectrodes, such as sensing electrodes 108A and 108B (individually orcollectively, “sensing electrode(s) 108”), located along the distalportion of defibrillation lead 102A. In the example illustrated in FIG.4A and FIG. 4B, sensing electrodes 108A and 108B are separated from oneanother by defibrillation electrode 106A. In other examples, however,sensing electrodes 108A and 108B may be both distal of defibrillationelectrode 106 or both proximal of defibrillation electrode 106. In otherexamples, lead 102A may include more or fewer electrodes at variouslocations proximal and/or distal to defibrillation electrode 106. In thesame or different examples, ICD 10C may include one or more electrodeson another lead (not shown).

ICD system 100A may sense electrical signals via one or more sensingvectors that include combinations of electrodes 108A and 108B and thehousing electrode of ICD 10C. In some instances, ICD 10C may sensecardiac electrical signals using a sensing vector that includes one ofthe defibrillation electrode sections 106A and 106B and one of sensingelectrodes 108A and 108B or the housing electrode of ICD 9. The sensedelectrical intrinsic signals may include electrical signals generated bycardiac muscle and indicative of depolarizations and repolarizations ofheart 16C at various times during the cardiac cycle. ICD 10C analyzesthe electrical signals sensed by the one or more sensing vectors todetect tachyarrhythmia, such as ventricular tachycardia or ventricularfibrillation. In response to detecting the tachyarrhythmia, ICD 10C maybegin to charge a storage element, such as a bank of one or morecapacitors, and, when charged, deliver one or more defibrillation pulsesvia defibrillation electrode 106 of defibrillation lead 102A if thetachyarrhythmia is still present.

Medical device system 8C also includes an IMD 10D, which is implantedwithin heart 16C and configured to deliver cardiac pacing to the heart,e.g., is an intracardiac pacing device (IPD). IMD 10D is referred to asIPD 10D hereafter. In the illustrated example, IPD 10D is implantedwithin the right ventricle of heart 16C. However, in other examples,system 8C may additionally or alternatively include one or more IPDs 10Dwithin other chambers of heart 16C, or similarly configured pacingdevices attached to an external surface of heart 16C (e.g., in contactwith the epicardium) such that the pacing device is disposed outside ofheart 16C.

IPD 10D is configured to sense electrical activity of heart 16C anddeliver pacing therapy, e.g., bradycardia pacing therapy, cardiacresynchronization therapy (CRT), anti-tachycardia pacing (ATP) therapy,and/or post-shock pacing, to heart 16C. IPD 10D may be attached to aninterior wall of heart 16C via one or more fixation elements thatpenetrate the tissue. These fixation elements may secure IPD 10D to thecardiac tissue and retain an electrode (e.g., a cathode or an anode) incontact with the cardiac tissue.

IPD 10D may be capable sensing electrical signals using the electrodescarried on the housing of IPD 10D. These electrical signals may beelectrical signals generated by cardiac muscle and indicative ofdepolarizations and repolarizations of heart 16C at various times duringthe cardiac cycle. IPD 10D may analyze the sensed electrical signals todetect bradycardia and tachyarrhythmias, such as ventricular tachycardiaor ventricular fibrillation. In response to detecting bradycardia, IPD10D may deliver bradycardia pacing via the electrodes of IPD 10D. Inresponse to detecting tachyarrhythmia, IPD 10D may, e.g., depending onthe type of tachyarrhythmia, deliver ATP therapy via the electrodes ofIPD 10D. In some examples, IPD 10D may deliver post-shock pacing inresponse to determining that another medical device, e.g., ICD 10C,delivered an anti-tachyarrhythmia shock.

IPD 10D and ICD 10C may be configured to coordinate their arrhythmiadetection and treatment activities. In some examples IPD 10D and ICD 10Cmay be configured to operate completely independently of one another. Insuch a case, IPD 10D and ICD 10C are not capable of establishingtelemetry communication sessions with one another to exchangeinformation about sensing and/or therapy using one-way or two-waycommunication. Instead, each of IPD 10D and ICD 10C analyze the datasensed via their respective electrodes to make tachyarrhythmia detectionand/or therapy decisions. As such, each device does not know if theother will detect the tachyarrhythmia, if or when it will providetherapy, and the like. In some examples, IPD 10D may be configured todetect anti-tachyarrhythmia shocks delivered by ICD system 100A, whichmay improve the coordination of therapy between subcutaneous ICD 10C andIPD 10D without requiring device-to-device communication. In thismanner, IPD 10D may coordinate the delivery of cardiac stimulationtherapy, including the termination of ATP and the initiation of thedelivery of post-shock pacing, with the application of ananti-tachyarrhythmia shock merely through the detection ofdefibrillation pulses and without the need to communicate with thedefibrillation device applying the anti-tachyarrhythmia shock.

In other examples, IPD 10D and ICD 10C may engage in communication tofacilitate the appropriate detection of arrhythmias and/or delivery oftherapy. The communication may include one-way communication in whichone device is configured to transmit communication messages and theother device is configured to receive those messages. The communicationmay instead include two-way communication in which each device isconfigured to transmit and receive communication messages. Two-waycommunication and coordination of the delivery of patient therapiesbetween IPD 10D and ICD 10C is described in commonly-assigned U.S. Pat.No. 8,744,572, titled, “SYSTEMS AND METHODS FOR LEADLESS PACING ANDSHOCK THERAPY,” issued Jun. 3, 2014, the entire content of which isincorporated by reference herein.

External device 30C may be configured substantially similarly toexternal device 30A described above with respect to FIG. 1. Externaldevice 30C may be configured to communicate with one or both of ICD 10Cand IPD 10D. In examples where external device 30C only communicateswith one of ICD 10C and IPD 10D, the non-communicative device mayreceive instructions from or transmit data to the device incommunication with external device 30C. In some examples, a user mayinteract with device 30C remotely via a networked computing device. Theuser may interact with external device 30C to communicate with IPD 10Dand/or ICD 10C.

For example, the user may interact with external device 30C to send aninterrogation request and retrieve sensed physiological data or therapydelivery data stored by one or both of ICD 10C and IPD 10D, and programor update therapy parameters that define therapy, or perform any otheractivities with respect to ICD 10C and IPD 10D. Although the user is aphysician, technician, surgeon, electrophysiologist, or other healthcareprofessional, the user may be patient 14C in some examples. For example,external device 21 may allow a user to program any coefficients,weighting factors, or techniques for determining difference metrics,scores, and/or thresholds, or other data described herein as being usedby a medical device system to determine whether an acute cardiac eventis predicted.

Although FIGS. 4A-4C are shown or described in the context of IPD 10Dand extracardiovascular ICD system 100A that includes lead 102A with asubsternally placed distal portion, techniques in accordance with one ormore aspects of the present disclosure may be applicable to othercoexistent systems. For example, an extracardiovascular ICD system mayinclude a lead having a distal portion that is implanted subcutaneouslyabove the sternum (or other location) instead of being implantedsubsternally. As another example, instead of an IPD, a pacing system maybe implanted having a pacemaker and one or more leads connected to andextending from the pacemaker into one or more chambers of the heart orattached to the outside of the heart to provide pacing therapy to theone or more chambers. As such, the example of FIGS. 4A-4C is illustratedfor example purposes only and should not be considered limiting of thetechniques described herein.

FIG. 5 is a conceptual drawing illustrating another example medicaldevice system 8D that includes an extracardiovascular ICD system 100Band IPD 10D implanted within a patient. Medical device system 8B may beconfigured to perform any of the techniques described herein withrespect to medical device system 8C of FIGS. 4A-4C. Components with likenumbers in FIGS. 4A-4C and FIG. 5 may be similarly configured andprovide similar functionality.

In the example of FIG. 5, extracardiovascular ICD system 100B includesICD 10C coupled to a defibrillation lead 102B. Unlike defibrillationlead 102A of FIGS. 4A-4C, defibrillation lead 102B extendssubcutaneously above the ribcage from ICD 10C. In the illustratedexample, defibrillation lead 102B extends toward a center of the torsoof patient 14D, bends or turns near the center of the torso, and extendssubcutaneously superior above the ribcage and/or sternum 110.Defibrillation lead 102B may be offset laterally to the left or theright of sternum 110 or located over sternum 110. Defibrillation lead102B may extend substantially parallel to sternum 102 or be angledlateral from the sternum at either the proximal or distal end.

Defibrillation lead 102B includes an insulative lead body having aproximal end that includes a connector 104 configured to be connected toICD 10C and a distal portion that includes one or more electrodes.Defibrillation lead 102B also includes one or more conductors that forman electrically conductive path within the lead body and interconnectthe electrical connector and respective ones of the electrodes. In theillustrated example, defibrillation lead 102B includes a singledefibrillation electrode 106 toward the distal portion of defibrillationlead 102B, e.g., toward the portion of defibrillation lead 102Bextending along sternum 110. Defibrillation lead 102B is placed alongsternum 110 such that a therapy vector between defibrillation electrode106 and a housing electrode formed by or on ICD 10C (or other secondelectrode of the therapy vector) is substantially across a ventricle ofheart 16D.

Defibrillation lead 102B may also include one or more sensingelectrodes, such as sensing electrodes 108A and 108B, located along thedistal portion of defibrillation lead 102B. In the example illustratedin FIG. 5, sensing electrodes 108A and 108B are separated from oneanother by defibrillation electrode 106. In other examples, however,sensing electrodes 108A and 108B may be both distal of defibrillationelectrode 106 or both proximal of defibrillation electrode 106. In otherexamples, lead 102B may include more or fewer electrodes at variouslocations proximal and/or distal to defibrillation electrode 106, andlead 102B may include multiple defibrillation electrodes, e.g.,defibrillation electrodes 106A and 106B as illustrated in the example ofFIGS. 4A-4C.

FIG. 6 is a conceptual drawing illustrating an example configuration ofIPD 10D. As shown in FIG. 6, IPD 10D includes case 130, cap 138,electrode 140, electrode 132, fixation mechanisms 142, flange 134, andopening 136. Together, case 130 and cap 138 may be considered thehousing of IPD 10D. In this manner, case 130 and cap 138 may enclose andprotect the various electrical components, e.g., circuitry, within IPD10D. Case 130 may enclose substantially all of the electricalcomponents, and cap 138 may seal case 130 and create the hermeticallysealed housing of IPD 10D. Although IPD 10D is generally described asincluding one or more electrodes, IPD 10D may typically include at leasttwo electrodes (e.g., electrodes 132 and 140) to deliver an electricalsignal (e.g., therapy such as cardiac pacing) and/or provide at leastone sensing vector.

Electrodes 132 and 140 are carried on the housing created by case 130and cap 138. In this manner, electrodes 132 and 140 may be consideredleadless electrodes. In the example of FIG. 6, electrode 140 is disposedon the exterior surface of cap 138. Electrode 140 may be a circularelectrode positioned to contact cardiac tissue upon implantation.Electrode 132 may be a ring or cylindrical electrode disposed on theexterior surface of case 130. Both case 130 and cap 138 may beelectrically insulating.

Electrode 140 may be used as a cathode and electrode 132 may be used asan anode, or vice versa, for delivering cardiac pacing such asbradycardia pacing, CRT, ATP, or post-shock pacing. However, electrodes132 and 140 may be used in any stimulation configuration. In addition,electrodes 132 and 140 may be used to detect intrinsic electricalsignals from cardiac muscle.

Fixation mechanisms 142 may attach IPD 10D to cardiac tissue. Fixationmechanisms 142 may be active fixation tines, screws, clamps, adhesivemembers, or any other mechanisms for attaching a device to tissue. Asshown in the example of FIG. 6, fixation mechanisms 142 may beconstructed of a memory material, such as a shape memory alloy (e.g.,nickel titanium), that retains a preformed shape. During implantation,fixation mechanisms 142 may be flexed forward to pierce tissue andallowed to flex back towards case 130. In this manner, fixationmechanisms 142 may be embedded within the target tissue.

Flange 134 may be provided on one end of case 130 to enable tethering orextraction of IPD 10D. For example, a suture or other device may beinserted around flange 134 and/or through opening 136 and attached totissue. In this manner, flange 134 may provide a secondary attachmentstructure to tether or retain IPD 10D within heart 16C (or 16D) iffixation mechanisms 142 fail. Flange 134 and/or opening 136 may also beused to extract IPD 10D once the IPD needs to be explanted (or removed)from patient 14D if such action is deemed necessary.

IPD 10D is one example of a pacing device configured to implement thetechniques of this disclosure. However, other implantable medicaldevices may be used to perform the same or similar functions as IPD 10D.For example, an IPD may include a small housing that carries anelectrode, similar to IPD 10D, and be configured to be implanted withina chamber of a heart 16. The IPD may also include one or more relativelyshort leads configured to place one or more respective additionalelectrodes at another location within the same chamber of the heart or adifferent chamber of the heart. In this manner, the housing of the IPDmay not carry all of the electrodes used to perform functions describedherein with respect to IPD 10D. In other examples, each electrode of theIPD may be carried by one or more leads (e.g., the housing of the IPDmay not carry any of the electrodes). In some examples, an IPD or otherpacing device may include or be coupled to three or more electrodes,where each electrode may deliver therapy and/or detect intrinsicsignals.

In another example, a pacing device may be configured to be implantedexternal to the heart, e.g., near or attached to the epicardium of theheart. An electrode carried by the housing of the pacing may be placedin contact with the epicardium and/or one or more electrodes of leadscoupled to the pacing may be placed in contact with the epicardium atlocations sufficient to provide cardiac pacing. In still other examples,a pacing device configured to perform the techniques described hereinmay be implanted subcutaneously or submuscularly, and connected to oneor more intracardiac leads carrying one or more electrodes.

Referring back to FIGS. 4A-5, medical device systems 8C and 8D areexamples of medical device systems configured to determine whether anacute occurrence of a cardiac event, such as a ventriculartachyarrhythmia, is predicted to occur, and to responsively provide analert indicating that the acute cardiac event is predicted, and/ordeliver a preventative measure, e.g., therapy, configured to prevent thepredicted cardiac event. The techniques may be performed by processingcircuitry of medical device system 8C or 8D, such as processingcircuitry of one or more of ICD 10C, IPD 10D, and external device 30C or30D, individually, or collectively. Although the example medical devicessystems 8C and 8D of FIGS. 4A-5 are illustrated as including both ICD10C and IPD 10D, other examples may include only one of ICD 10C or IPD10D, alone, or in combination with other implanted or external devices.

The techniques include determining a respective value for each of aplurality of patient parameters of a patient during each of a pluralityof periods, which may be at least one hour, such as approximately oneday. The processing circuitry may determine the values of at least somethe patient parameters based on physiological signals generated bysensing circuitry of one or both of ICD 10C and IPD 10D, such as cardiacEGM signals generated by sensing circuitry of the IMDs. In someexamples, one or both of ICD 10C and IPD 10D may include or be coupledto one or more other sensors that generate one or more otherphysiological signals, such as signals that vary based on patient motionand/or posture, blood flow, blood pressure (e.g., systems 8C and 8D mayinclude pressure sensing IMD 50, described above with respect to FIG.1), respiration, or edema. The processing circuitry may determine otherpatient parameters based on therapies delivered by ICD 10C and/or IPD10D, such as patient parameters indicating the extent to which patient14C or 14D is dependent on pacing, e.g., a percentage of time or othercharacterization of amount of pacing delivered to the patient, or thenumber of anti-tachyarrhythmia therapies delivered to the patient.

In some examples, the processing circuitry of medical device system 8Cor 8D indicates that the acute cardiac event is predicted if thecumulative degree of change, across the patient parameters during thecurrent period is significantly greater than the variation in thepatient parameters during N recently preceding periods. For example, aswill be described in greater detail below, the processing circuitry maydetermine, for each of a plurality of patient parameters, a differencemetric for a current period based on a value of a patient parameterdetermined for the current period and a value of the patient parameterdetermined for an immediately preceding period. In some examples, theprocessing circuitry determines a score for the current period based ona sum of the difference metrics for the current period for at least someof the plurality of patient parameters. The processing circuitrydetermines a threshold for the current period based on scores determinedfor N periods that precede the current period, and compares the scorefor the current period to the threshold for the current period todetermine whether the acute event is predicted. If the processingcircuitry determines that the acute cardiac event is predicted, theprocessing circuitry may generate an alert and, in some examples,control delivery of one or more preventative measures configured toprevent the event, such as cardiac pacing, neuromodulation, or one ormore therapeutic substances, e.g., drugs.

FIG. 7 is a functional block diagram illustrating an exampleconfiguration of an IMD 10. IMD 10 may correspond to any of ICD 10A, ICM10B, ICD 10C, IPD 10D, or another IMD configured to implement thetechniques for predicting an acute cardiac event described in thisdisclosure. In the illustrated example, IMD 10 includes processingcircuitry 160 and an associated memory 170, sensing circuitry 162,therapy delivery circuitry 164, one or more sensors 166, andcommunication circuitry 168. However, ICD 10A, ICM 10B, ICD 10C, and IPD10D need not include all of these components, or may include additionalcomponents. For example, ICM 10B may not include therapy deliverycircuitry 164, in some examples.

Memory 170 includes computer-readable instructions that, when executedby processing circuitry 160, cause IMD 10 and processing circuitry 160to perform various functions attributed to IMD 10 and processingcircuitry 160 herein (e.g., determining patient parameter values,difference metrics, scores and thresholds, and determining whether toprovide an alert indicating that an acute cardiac event is predicted).Memory 170 may include any volatile, non-volatile, magnetic, optical, orelectrical media, such as a random access memory (RAM), read-only memory(ROM), non-volatile RAM (NVRAM), electrically-erasable programmable ROM(EEPROM), flash memory, or any other digital or analog media.

Processing circuitry 160 may include fixed function circuitry and/orprogrammable processing circuitry. Processing circuitry 160 may includeany one or more of a microprocessor, a controller, a digital signalprocessor (DSP), an application specific integrated circuit (ASIC), afield-programmable gate array (FPGA), or equivalent discrete or analoglogic circuitry. In some examples, processing circuitry 160 may includemultiple components, such as any combination of one or moremicroprocessors, one or more controllers, one or more DSPs, one or moreASICs, or one or more FPGAs, as well as other discrete or integratedlogic circuitry. The functions attributed to processing circuitry 160herein may be embodied as software, firmware, hardware or anycombination thereof.

Sensing circuitry 162 and therapy delivery circuitry 164 are coupled toelectrodes 190. Electrodes 190 illustrated in FIG. 7 may correspond to,for example: electrodes 12, 22, 24, 26, 28, 44, and 44 of ICD 10A (FIG.1); electrodes 64 and 66 of ICM 10B (FIG. 3); electrodes 106, 108, andone or more housing electrodes of ICD 10C (FIGS. 4A-5); or electrodes132 and 140 of IPD 10D (FIG. 6).

Electrical sensing circuitry 162 monitors signals from a selected two ormore of electrodes 190 in order to monitor electrical activity of heart26, impedance, or other electrical phenomenon. Sensing of a cardiacelectrical signal may be done to determine heart rates or heart ratevariability, or to detect arrhythmias (e.g., tachyarrhythmias orbradycardia) or other electrical signals. In some examples, sensingcircuitry 162 may include one or more filters and amplifiers forfiltering and amplifying a signal received from electrodes 190.

The resulting cardiac electrical signal may be passed to cardiac eventdetection circuitry that detects a cardiac event when the cardiacelectrical signal crosses a sensing threshold. The cardiac eventdetection circuitry may include a rectifier, filter and/or amplifier, asense amplifier, comparator, and/or analog-to-digital converter. Sensingcircuitry 162 outputs an indication to processing circuitry 160 inresponse to sensing of a cardiac event (e.g., detected P-waves orR-waves).

In this manner, processing circuitry 160 may receive detected cardiacevent signals corresponding to the occurrence of detected R-waves andP-waves in the respective chambers of heart 26. Indications of detectedR-waves and P-waves may be used for detecting ventricular and/or atrialtachyarrhythmia episodes, e.g., ventricular or atrial fibrillationepisodes. Some detection channels may be configured to detect cardiacevents, such as P- or R-waves, and provide indications of theoccurrences of such events to processing circuitry 160, e.g., asdescribed in U.S. Pat. No. 5,117,824 to Keimel et al., which issued onJun. 2, 1992 and is entitled, “APPARATUS FOR MONITORING ELECTRICALPHYSIOLOGIC SIGNALS,” and is incorporated herein by reference in itsentirety.

Sensing circuitry 162 may also include a switch module to select whichof the available electrodes 190 (or electrode polarities) are used tosense the heart activity. In examples with several electrodes 190,processing circuitry 160 may select the electrodes that function assense electrodes, i.e., select the sensing configuration, via the switchmodule within sensing circuitry 162. Sensing circuitry 162 may also passone or more digitized EGM signals to processing circuitry 160 foranalysis, e.g., for use in cardiac rhythm discrimination.

Processing circuitry 160 may implement programmable counters. If IMD 10is configured to generate and deliver pacing pulses to heart 26, suchcounters may control the basic time intervals associated withbradycardia pacing (e.g., DDD, VVI, DVI, VDD, AAI, DDI, DDDR, VVIR,DVIR, VDDR, AAIR, DDIR pacing) and other modes of pacing. Intervalsdefined by processing circuitry 160 may include atrial and ventricularpacing escape intervals, refractory periods during which sensed P-wavesand R-waves are ineffective to restart timing of the escape intervals,and the pulse widths of the pacing pulses. The durations of theseintervals may be determined by processing circuitry 160 in response topacing mode parameters stored in memory 170.

Interval counters implemented by processing circuitry 160 may be resetupon sensing of R-waves and P-waves with detection channels of sensingcircuitry 162, or upon the generation of pacing pulses by therapydelivery circuitry 164, and thereby control the basic timing of cardiacpacing functions, including bradycardia pacing, CRT, ATP, or post-shockpacing. The value of the count present in the interval counters whenreset by sensed R-waves and P-waves may be used by processing circuitry160 to measure the durations of R-R intervals, P-P intervals, P-Rintervals, and R-P intervals, which are measurements that may be storedin memory 170. Processing circuitry 160 may use the count in theinterval counters to detect a tachyarrhythmia event, such as atrialfibrillation (AF), atrial tachycardia (AT), VF, or VT. These intervalsmay also be used to detect the overall heart rate, ventricularcontraction rate, and heart rate variability. A portion of memory 170may be configured as a plurality of recirculating buffers, capable ofholding series of measured intervals, which may be analyzed byprocessing circuitry 160 in response to the occurrence of a pace orsense interrupt to determine whether the patient's heart 26 is presentlyexhibiting atrial or ventricular tachyarrhythmia.

In some examples, an arrhythmia detection method may include anysuitable tachyarrhythmia detection algorithms. In one example,processing circuitry 160 may utilize all or a subset of the rule-baseddetection methods described in U.S. Pat. No. 5,545,186 to Olson et al.,entitled, “PRIORITIZED RULE BASED METHOD AND APPARATUS FOR DIAGNOSIS ANDTREATMENT OF ARRHYTHMIAS,” which issued on Aug. 13, 1996, or in U.S.Pat. No. 5,755,736 to Gillberg et al., entitled, “PRIORITIZED RULE BASEDMETHOD AND APPARATUS FOR DIAGNOSIS AND TREATMENT OF ARRHYTHMIAS,” whichissued on May 26, 1998. U.S. Pat. No. 5,545,186 to Olson et al. U.S.Pat. No. 5,755,736 to Gillberg et al. is incorporated herein byreference in their entireties. However, other arrhythmia detectionmethodologies, such as those methodologies that utilize timing andmorphology of the electrocardiogram, may also be employed by processingcircuitry 160 in other examples.

In some examples, processing circuitry 160 may determine thattachyarrhythmia has occurred by identification of shortened R-R (or P-P)interval lengths. Generally, processing circuitry 160 detectstachycardia when the interval length falls below 220 milliseconds andfibrillation when the interval length falls below 180 milliseconds. Inother examples, processing circuitry 160 may detect ventriculartachycardia when the interval length falls between 330 milliseconds andventricular fibrillation when the interval length falls below 240milliseconds. These interval lengths are merely examples, and a user maydefine the interval lengths as desired, which may then be stored withinmemory 170. This interval length may need to be detected for a certainnumber of consecutive cycles, for a certain percentage of cycles withina running window, or a running average for a certain number of cardiaccycles, as examples. In other examples, additional patient parametersmay be used to detect an arrhythmia. For example, processing circuitry160 may analyze one or more morphology measurements, impedances, or anyother physiological measurements to determine that patient 14 isexperiencing a tachyarrhythmia.

In addition to detecting and identifying specific types of cardiacevents, e.g., cardiac depolarizations, sensing circuitry 162 may alsosample the detected intrinsic signals to generate an electrogram orother time-based indication of cardiac events. Sensing circuitry 162 mayinclude an analog-to-digital converter or other circuitry configured tosample and digitize the electrical signal sensed via electrodes 190.Processing circuitry 160 may analyze the digitized signal for a varietyof purposes, including morphological identification or confirmation oftachyarrhythmia of heart 26. As another example, processing circuitry160 may analyze the digitized cardiac electrogram signal to identify andmeasure a variety of morphological features of the signal. As describedin greater detail below, the morphological features of the cardiacelectrogram may be patient parameters, and their measurements patientparameter values, used to determine whether an acute cardiac event,e.g., ventricular tachyarrhythmia, is predicted to occur.

In some examples, sensing circuitry 162 is configured to sense otherphysiological signals of patient. For example, sensing circuitry 162 maybe configured to sense signals that vary with changing thoracicimpedance of patient 14. The thoracic impedance may vary based on fluidvolume or edema in patient 14.

Sensing circuitry 162 may use any two or more of electrodes 190 to sensethoracic impedance. As the tissues within the thoracic cavity of patient14 change in fluid content, the impedance between two electrodes mayalso change. For example, the impedance between a defibrillation coilelectrode (42, 44, 106) and the housing electrode may be used to monitorchanging thoracic impedance.

In some examples, processing circuitry 160 measured thoracic impedancevalues to determine a fluid index. As more fluid is retained withinpatient 14, e.g., edema increases, and the thoracic impedance decreasesor remains relatively high, the fluid index increases. Conversely, asthe thoracic impedance increases or remains relatively low, the fluidindex decreases. An example system for measuring thoracic impedance anddetermining a fluid index is described in U.S. Pat. No. 8,255,046 toSarkar et al., entitled, “DETECTING WORSENING HEART FAILURE BASED ONIMPEDANCE MEASUREMENTS,” which issued on Aug. 28, 2012 and isincorporated herein by reference in its entirety.

The thoracic impedance may also vary with patient respiration. In someexamples, processing circuitry 160 may determine values of one or morerespiration-related patient parameters based on thoracic impedancesensed by sensing circuitry 162. Respiration-related patient parametersmay include, as examples, respiration rate, respiration depth, or theoccurrence or magnitude of dyspnea or apneas.

The magnitude of the cardiac electrogram may also vary based on patientrespiration, e.g., generally at a lower frequency than the cardiaccycle. In some examples, processing circuitry 160 and/or sensingcircuitry 162 may filter the cardiac electrogram to emphasize therespiration component of the signal. Processing circuitry 160 mayanalyze the filtered cardiac electrogram signal to determine values ofrespiration-related patient parameters.

In the example of FIG. 7, IMD 10 includes one or more sensors 166coupled to sensing circuitry 162. Although illustrated in FIG. 7 asincluded within IMD 10, one or more of sensors 166 may be external toIMD 10, e.g., coupled to IMD 10 via one or more leads, or configured towirelessly communicate with IMD 10. In some examples, sensors 166transduce a signal indicative of a patient parameter, which may beamplified, filtered, or otherwise processed by sensing circuitry 162. Insuch examples, processing circuitry 160 determines values of patientparameters based on the signals. In some examples, sensors 166 determinethe patient parameter values, and communicate them, e.g., via a wired orwireless connection, to processing circuitry 160.

In some examples, sensors 166 include one or more accelerometers, e.g.,one or more 3-axis accelerometers. Signals generated by the one or moreaccelerometers may be indicative of, as examples, gross body movement(e.g., activity) of patient 14, patient posture, heart sounds or othervibrations or movement associated with the beating of the heart, orcoughing, rales, or other respiration abnormalities. In some examples,sensors 166 include one or more microphones configured to detect heartsounds or respiration abnormalities, and/or other sensors configured todetect patient activity or posture, such as gyroscopes and/or straingauges. In some examples, sensors 166 may include sensors configured totransduce signals indicative of blood flow, oxygen saturation of blood,or patient temperature, and processing circuitry 160 may determinepatient parameters values based on these signals.

In some examples, sensors 166 include one or more pressure sensors thattransduce one or more signals indicative of blood pressure, andprocessing circuitry 160 determines one or more patient parameter valuesbased on the pressure signals. Patient parameter values determined basedon pressure may include, as examples, systolic or diastolic pressurevalues, such as pulmonary artery diastolic pressure values. In someexamples, a separate pressure-sensing IMD 50 includes one or moresensors and sensing circuitry configured to generate a pressure signal,and processing circuitry 160 determines patient parameter values relatedto blood pressure based on information received from IMD 50.

Therapy delivery circuitry 164 is configured to generate and deliverelectrical therapy to the heart. Therapy delivery circuitry 164 mayinclude one or more pulse generators, capacitors, and/or othercomponents capable of generating and/or storing energy to deliver aspacing therapy, defibrillation therapy, cardioversion therapy, othertherapy, or a combination of therapies. In some instances, therapydelivery circuitry 164 may include a first set of components configuredto provide pacing therapy and a second set of components configured toprovide anti-tachyarrhythmia shock therapy. In other instances, therapydelivery circuitry 164 may utilize the same set of components to provideboth pacing and anti-tachyarrhythmia shock therapy. In still otherinstances, therapy delivery circuitry 164 may share some of the pacingand shock therapy components while using other components solely forpacing or shock delivery.

Therapy delivery circuitry 164 may include charging circuitry, one ormore charge storage devices, such as one or more capacitors, andswitching circuitry that controls when the capacitor(s) are dischargedto electrodes 190 and the widths of pulses. Charging of capacitors to aprogrammed pulse amplitude and discharging of the capacitors for aprogrammed pulse width may be performed by therapy delivery circuitry164 according to control signals received from processing circuitry 160,which are provided by processing circuitry 160 according to parametersstored in memory 170. Processing circuitry 160 controls therapy deliverycircuitry 164 to deliver the generated therapy to the heart via one ormore combinations of electrodes 190, e.g., according to parametersstored in memory 170. Therapy delivery circuitry 164 may include switchcircuitry to select which of the available electrodes 190 are used todeliver the therapy, e.g., as controlled by processing circuitry 160.

In some examples, IMD 10 may additionally or alternatively be configuredto deliver other therapies configured to prevent the predicted acutecardiac event. For example, processing circuitry 160 may control therapydelivery circuitry 164 to deliver cardiac pacing therapy configured toprevent a ventricular tachyarrhythmia, such as overdrive pacing therapywhen one or more of the patient parameters 174 indicate that the heartrate is not fast or down-drive pacing therapy if one or more of thepatient parameters 174 indicate that the heart rate is too fast.

As another example, IMD 10 may additionally or alternatively beconfigured to deliver neuromodulation therapy to prevent an acutecardiac event, such as ventricular tachyarrhythmia, heart failuredecompensation, or ischemia. In such examples, processing circuitry 160may be programmed, and therapy delivery circuitry 164 and electrodes 190configured and placed, to generate and deliver the neuromodulationtherapy. Example neuromodulation therapies include vagal nervestimulation, spinal cord stimulation, peripheral nerve stimulation,cardiac intrinsic nerve modulation, and cardiac stellate ganglionstimulation.

As another example, IMD 10 may additionally or alternatively beconfigured to deliver a therapeutic substance, e.g., infuse a drug. Insuch examples, IMD 10 may include a pump to deliver the substance, andprocessing circuitry 160 may be configured to control the pump accordingto therapy parameters stored in memory 170. Examples of delivery oftherapy substances to prevent an acute cardiac event include delivery ofsubstances that modulate the cardiovascular or neurological systems ofthe patient.

According to the acute cardiac event detection techniques describedherein, processing circuitry 160 periodically, i.e., for each of aplurality of periods, determines a respective value for each of aplurality of patient parameters. The determined patient parameter valuesare stored as patient parameter values 174 in memory 170. In someexamples, the length of each period is greater than one hour, such as apredetermined integer number of hours or days. In some examples, theperiod length is between eight hours and three days, such as one day.

Each of patient parameter values 174 may be the single value of apatient parameter determined during the period. In other examples, eachof patient parameter values 174 is a representative value determinedbased on a plurality of values determined during the period. In someexamples, patient parameter values 174 may include one or more means,medians, modes, sums, or other values determined based on a plurality ofvalues of a patient parameter determined during the period.

The plurality of patient parameters may include one or more parametersdetermined based on the cardiac electrogram, such as one or more heartrate parameters, and/or one or more tachyarrhythmia episode parameters.Example heart rate parameters include average heart rate during theperiod, average daytime heart rate during the period, average nighttimeheartrate during the period, and one or more measures of heart ratevariability during the period. Example tachyarrhythmia episodeparameters include the number, frequency and/or duration (total, mean,or median) of tachyarrhythmia episodes during the period, such as atrialtachycardia episodes, atrial fibrillation episodes, or non-sustainedtachyarrhythmia (NST) episodes. NST episodes may be a series of shortR-R intervals greater than an NST threshold number of short R-Rintervals, but fewer than a number of intervals to detect (NID) forventricular tachyarrhythmia. Another example patient parameter thatprocessing circuitry 160 may determine based on the cardiac electrogramis the ventricular rate during atrial tachyarrhythmia, e.g., atrialfibrillation, which may be a mean or median value during the period.

Other patient parameters determined based on the cardiac electrograminclude morphological features of the cardiac electrogram, such as QRSwidth or duration, QT interval length, T-wave amplitude, R-R intervallength, an interval between a peak and the end of the T-wave, a ratiobetween the T-wave peak to end interval and the QT interval lengths, orT-wave alternan. The presence of T-wave alternan may be detected as aperiodic (e.g., beat-to-beat) variation in the amplitude or morphologyof the T-wave. A T-wave alternan patient parameter value 174 may be anindication of the presence, number, frequency, or duration (total, mean,or median) of T-wave alternan episodes. Other patient parameter values174 based cardiac electrogram morphological interval lengths may bemeans or medians of a plurality of measurements made during the period,e.g., daily mean or median values.

The plurality of patient parameters may additionally or alternativelyinclude at least one patient parameter indicative of edema, andprocessing circuitry 160 may determine values 174 of such patientparameters based on sensed thoracic impedance, as described above. Insome examples, a patient parameter value 174 may be a maximum, minimum,mean, or median thoracic impedance value during a period. In someexamples, a patient parameter value 174 may be a fluid index valueduring the period. Processing circuitry 160 may increment and decrementa fluid index value based on an accumulation of differences between athoracic impedance value (or short-term average of impedance values) anda threshold determined based on a long-term average of thoracicimpedance values.

The plurality of patient parameters may additionally or alternativelyinclude at least one patient parameter indicative of patient activity,e.g., gross patient body movement or motion. In some examples,processing circuitry 160 determines a number of activity counts based onone or more accelerometer signals crossing (e.g., exceeding) one or morethresholds. A patient parameter value 174 during a period may be atotal, mean, or median number of counts during the period.

The plurality of patient parameters may additionally or alternativelyinclude at least one patient parameter indicative of cardiovascularpressure, and processing circuitry 160 may determine values 174 of suchpatient parameters based on generated pressure waveform, e.g., generatedby a sensor 166 or pressure-sensing IMD 50, as described above. Thepatient parameter values 174 for the period may include a maximum,minimum, mean, or median of systolic pressure and/or diastolic pressure,e.g., pulmonary artery diastolic pressure.

The plurality of patient parameters may additionally or alternativelyinclude at least one patient parameter determined based on patientrespiration, and processing circuitry 160 may determine values 174 ofsuch parameters based on a generated signal that varies based onrespiration as described above, such as a signal that varies based onthoracic impedance. The patient parameter values 174 for the period mayinclude a maximum, minimum, mean, or median of respiration rate, e.g.,for a day, daytime, or nighttime. The patient parameter values 174 forthe period may include an indication of the presence, a number, afrequency, or a duration (total, mean, or median) of respirationepisodes, such as apneas or dyspneas.

Processing circuitry 160 may additionally or alternatively determinevalues 174 of one or more patient parameters based on a generated signalthat varies based on sound or other vibrations, which may indicate heartsounds, coughing, or rales. Patient parameter values may includemorphological measurements of the S1 and S2 heart sounds, the presenceor frequency of occurrence of S3 and/or S4 heart sounds, or thepresence, number, frequency, or duration (total, mean, or median) ofepisodes or coughing or rales. Other patient parameter values 174 thatprocessing circuitry 160 may additionally or alternatively periodicallydetermine based on signals generated by sensors 166 include maximum,minimum, mean, or median values of blood flow, blood oxygen saturation,or temperature.

The plurality of patient parameters may additionally or alternativelyinclude at least one patient parameter determined based on delivery oftherapy to patient 14, e.g., by IMD 10. In some examples, a patientparameter value 174 for a period indicates an amount of cardiac pacingdelivered to the patient during the period, such as a total duration orpercentage of the period during which atrial pacing, ventricular pacing,and/or CRT was delivered.

In some examples, the plurality of patient parameter values 174determined for each period includes: a percentage of the period duringwhich IMD 10 delivered ventricular pacing to patient 14; a percentage ofthe period during which IMD 10 delivered atrial pacing to patient 14; anaverage daytime ventricular heart rate; an average nighttime ventricularheart rate; a frequency or duration of atrial tachycardia event, atrialfibrillation events, and/or NSTs during the period; a total number ofpatient activity counts during the period; a measure of heart ratevariability during the period; a daily thoracic impedance value; and afluid index value. In some examples, the plurality of patient parametervalues 174 includes all or subset of the parameters included in CardiacCompass® trends generated by IMDs available from Medtronic, plc, ofDublin Ireland. In some examples, the plurality of patient parametervalues 174 additionally includes one or more cardiac electrogrammorphology parameters.

Processing circuitry 160 determines a difference metric 176 for each ofthe plurality patient parameters for the period. Processing circuitry160 determines the difference metric 176 for each patient parameterbased on a difference between a current value 174 of the patientparameter for the current period, and an immediately preceding value 174of the patient parameter for the immediately preceding period. In someexamples, processing circuitry 160 determines the difference metric 176for each of the patient parameters according to the following equation:ΔV _(t,param) _(n) =Value_(t−1)−Value_(t−2)  (Eq. 1)

In some examples, the difference metric may be referred to as “ΔV_(t)”such as in Equation 1, or may be referred to as “V_(t)” such as inEquation 2 below. The difference metric may be indicative of dailychanges in values of risk factors, for example. In some examples,processing circuitry 160 determines the difference metric 176 for eachof the plurality patient parameters for the period based on thedifference between the current and preceding values, and a standarddeviation (or other measure of variation) of values 174 of the patientparameter for N preceding periods. N is an integer constant, e.g.,between 5 and 50, such as between 7 and 15 or, in one example, 15. Inexamples in which each period is a day, the N preceding periods may be Npreceding days. Determining the difference metric based on thedifference between the current and preceding values and a standarddeviation or other measure of variation allow the difference metric tobetter represent the difference in the patient parameter during thecurrent period rather than baseline variation of the patient parameterand/or noise. In some examples, processing circuitry 160 determines thedifference metric 176 for each of the patient parameters according tothe following equation:

$\begin{matrix}{V_{t,{param}_{n}} = \frac{{Value}_{\;{t - 1}} - {Value}_{\;{t - 2}}}{{SD}_{t}}} & \left( {{Eq}.\mspace{14mu} 2} \right)\end{matrix}$

Processing circuitry 160 determines a score 178 for the period based onthe plurality of patient parameter-specific difference metrics 176 forthe period. In some examples, processing circuitry 160 determines thescore 178 for the period based on a sum of squares of the differencemetrics 176 for the period or a sum of absolute values of the differencemetrics 176. The difference metrics 176 may be positive or negative, anduse of the sum of squares or absolute values may enable the score 178 toreflect the absolute magnitudes of change of the plurality of patientparameters during the period. In some examples, processing circuitry 160determines the score 178 for the period using a sum of squares ofdifference metrics 176 according to the following equation, where n isthe number of patient parameters for which difference metrics 176 aredetermined during the period (in this case 8):Score_(t)=Σ_(n=1) ⁸ V_(t,param) _(n) ²  (Eq. 3)

In some examples, processing circuitry 160 applies coefficients orweights to one or more of difference metrics 176 when determining ascore 178 for a period, such as in Equation 4 below. The weights may bedetermined and/or adjusted empirically based on an analysis of thesensitivity and specificity of the score 178 in predicting occurrence ofacute cardiac events over time for patient 14 or population of patients,e.g., having similar characteristics to patient 14. The values of theweights may be adjusted over time, e.g., on a period-by-period or lessfrequent basis.Score_(t)=Σ_(n=1) ⁸ α_(n) |ΔV _(t,param) _(n) |  (Eq. 4)

The score of Equation 4 may be indicative of the weighted risk scorebased on pathophysiological changes. An example of a coefficient orweight, as described above, may include “α_(n)” as in Equation 4. α_(n)may be a wright constant, such that the moving window size, silenceinterval, threshold setting, and prediction window may be betteroptimized. In an example, a may be a value that is based on findingsfrom previous research, event history from an individual or more thanone individual, or other factors. For example, T-wave alternans may berelevant to an arrhythmic event. As such, the difference value of T wavealternans may be weighted up (e.g., 5 μV weighted to 5×10). In anexample, if a previous event occurred when thoracic impedance wasrelatively high, then the change value for impedance can be weightedhigher. On the other hand, for example, some changes may be good changesthat may be weighted smaller or assigned zero weight (e.g., no risk,such as an increase in HRV or HRV above a particular value, such asabout 80 ms).

Processing circuitry 160 also determines a threshold 180 for the periodbased on scores 178 for N preceding periods, wherein N is the integerconstant, e.g., 15. In some examples, processing circuitry 160determines the threshold 180 based on a mean or median of the Npreceding scores, e.g., by multiplying a median of the N scores and acoefficient. The coefficient may be, for example, between 1 and 3, anddetermined for a given patient 14 or patient population based on areceiver operator characteristic (ROC).

Processing circuitry 160 compares the score for the period to thethreshold for the period. If the score exceeds the threshold, e.g., isgreater than, or greater than or equal to the threshold, processingcircuitry 160 provides an alert that a cardiac event, e.g., aventricular tachyarrhythmia, is predicted to acutely occur. In someexamples, processing circuitry 160 may additionally control therapydelivery circuitry 162, a pump included in IMD 10, or another implantedor external medical device to deliver a therapy configured to preventthe acute cardiac event, such as a pacing therapy, a neuromodulationtherapy, or a therapeutic substance. In some examples, a clinician mayprescribe or deliver, or control another device to deliver, such atherapy based on the alert generated by processing circuitry 160.

Communication circuitry 168 includes any suitable hardware, firmware,software, or any combination thereof for communicating with anotherdevice, such as an external device 30 or another IMD or sensor. Underthe control of processing circuitry 160, communication circuitry 168 mayreceive downlink telemetry from and send uplink telemetry to externaldevice 30 or another device with the aid of an antenna, which may beinternal and/or external. In some examples, communication circuitry 168may communicate with a local external device, and processing circuitry160 may communicate with a networked computing device via the localexternal device and a computer network, such as the Medtronic CareLink®Network developed by Medtronic, plc, of Dublin, Ireland.

A clinician or other user may retrieve data from IMD 10 using externaldevice 30 or another local or networked computing device configured tocommunicate with processing circuitry 160 via communication circuitry168. The clinician may also program parameters of IMD 10 using externaldevice 30 or another local or networked computing device. In someexamples, the clinician may select patient parameters used to predictacute cardiac events, select values for a coefficient used to determinethreshold 180, select a value for the number of N preceding periods, andreceive alerts that indicate that the acute cardiac event is predictedvia communication circuitry 168 and external device 130 and/or anothercomputing device.

FIG. 8 is a functional block diagram illustrating an exampleconfiguration of an external device 30 configured to communicate withone or more IMDs 10. In the example of FIG. 8, external device 30includes processing circuitry 200, memory 202, user interface (UI) 204,and communication circuitry 206. External device 30 may correspond toany of external devices 30A-30C described with respect to FIGS. 1, 2,and 4A-5. External device 30 may be a dedicated hardware device withdedicated software for the programming and/or interrogation of an IMD10. Alternatively, external device 30 may be an off-the-shelf computingdevice, e.g., running an application that enables external device 30 toprogram and/or interrogate IMD 10.

In some examples, a user uses external device 30 to select or programany of the values for operational parameters of IMD 10, e.g., forpatient parameter sensing, therapy delivery, and acute cardiac eventprediction. In some examples, a user uses external device 30 to receivedata collected by IMD 10, such as patient parameter values 174 or otheroperational and performance data of IMD 10. The user may also receivealerts provided by IMD 10 that indicate that an acute cardiac event,e.g., ventricular tachyarrhythmia, is predicted. The user may interactwith external device 30 via UI 204, which may include a display topresent a graphical user interface to a user, and a keypad or anothermechanism (such as a touch sensitive screen) for receiving input from auser. External device 30 may communicate wirelessly with IMD 10 usingcommunication circuitry 206, which may be configured for RFcommunication with communication circuitry 168 of IMD 10.

Processing circuitry 200 may include any combination of integratedcircuitry, discrete logic circuitry, analog circuitry, such as one ormore microprocessors, digital signal processors (DSPs), applicationspecific integrated circuits (ASICs), or field-programmable gate arrays(FPGAs). In some examples, processing circuitry 200 may include multiplecomponents, such as any combination of one or more microprocessors, oneor more DSPs, one or more ASICs, or one or more FPGAs, as well as otherdiscrete or integrated logic circuitry, and/or analog circuitry.

Memory 202 may store program instructions, which may include one or moreprogram modules, which are executable by processing circuitry 200. Whenexecuted by processing circuitry 200, such program instructions maycause processing circuitry 200 and external device 30 to provide thefunctionality ascribed to them herein. The program instructions may beembodied in software, firmware and/or RAMware. Memory 202 may includeany volatile, non-volatile, magnetic, optical, or electrical media, suchas a random access memory (RAM), read-only memory (ROM), non-volatileRAM (NVRAM), electrically-erasable programmable ROM (EEPROM), flashmemory, or any other digital media.

In some examples, processing circuitry 200 of external device 30 may beconfigured to provide some or all of the functionality ascribed toprocessing circuitry 160 of IMD 10 herein. For example, processingcircuitry 200 may receive physiological signals generated by one or moreIMDs 10 and determine values 174 of each of a plurality of patientparameters during each of a plurality of periods, and/or may receivepatient parameter values 174 for the plurality of periods from one ormore IMDs 10. Processing circuitry 200 may determine difference metrics176, scores 178, and thresholds 180 based on the patient parametervalues 174 in the manner described above with respect to processingcircuitry 160 of IMD 10. Processing circuitry 200 may also comparescores 178 to thresholds 180 and generate an alert and/or controldelivery of preventative therapy by one or more implanted or externalmedical devices in the manner described above with respect to processingcircuitry 160 of IMD 10. Processing circuitry 200 may provide an alertto a user via UI 204, or via another device with which processingcircuitry 200 communicates via communication circuitry 206.

FIG. 9 is a functional block diagram 218 illustrating an example systemthat includes external computing devices, such as a server 224 and oneor more other computing devices 230A-230N, that are coupled to IMD 10and external device 30 via a network 222. In this example, IMD 10 mayuse its communication module 168 to, e.g., at different times and/or indifferent locations or settings, communicate with external device 30 viaa first wireless connection, and to communication with an access point220 via a second wireless connection. In the example of FIG. 9, accesspoint 220, external device 30, server 224, and computing devices230A-230N are interconnected, and able to communicate with each other,through network 222.

Access point 220 may comprise a device that connects to network 222 viaany of a variety of connections, such as telephone dial-up, digitalsubscriber line (DSL), or cable modem connections. In other examples,access point 220 may be coupled to network 222 through different formsof connections, including wired or wireless connections. In someexamples, access point 220 may be co-located with patient 14. Accesspoint 220 may interrogate IMD 10, e.g., periodically or in response to acommand from patient 14 or network 222, to retrieve physiologicalsignals, patient parameter values 174, difference metrics 176, scores178, thresholds 180, alerts of acute cardiac events, and/or otheroperational or patient data from IMD 10. Access point 220 may providethe retrieved data to server 224 via network 222.

In some cases, server 224 may be configured to provide a secure storagesite for data that has been collected from IMD 10 and/or external device30. In some cases, server 224 may assemble data in web pages or otherdocuments for viewing by trained professionals, such as clinicians, viacomputing devices 230A-230N. The illustrated system of FIG. 9 may beimplemented, in some aspects, with general network technology andfunctionality similar to that provided by the Medtronic CareLink®Network developed by Medtronic plc, of Dublin, Ireland.

In some examples, one or more of access point 220, server 224, orcomputing devices 230 may be configured to perform, e.g., may includeprocessing circuitry configured to perform, some or all of thetechniques described herein, e.g., with respect to processing circuitry160 of IMD 10 and processing circuitry 200 of external device 30,relating to prediction of acute cardiac events, such as ventriculartachyarrhythmia. In the example of FIG. 9, server 224 includes a memory226 to store physiological signals or patient parameter values 174received from IMD 10 and/or external device 30, and processing circuitry228, which may be configured to provide some or all of the functionalityascribed to processing circuitry 160 of IMD 10 and processing circuitry200 of external device 30 herein. For example, processing circuitry 228may determine values 174 of each of a plurality of patient parametersduring each of a plurality of periods, and/or may receive patientparameter values 174 for the plurality of periods from one or more IMDs10. Processing circuitry 228 may determine difference metrics 176,scores 178, and thresholds 180 based on the patient parameter values 174in the manner described above with respect to processing circuitry 160of IMD 10. Processing circuitry 227 may also compare scores 178 tothresholds 180 and generate an alert and/or control delivery ofpreventative therapy by one or more implanted or external medicaldevices in the manner described above with respect to processingcircuitry 160 of IMD 10. Processing circuitry 228 may provide an alertto a user via network 222, e.g., via external device 30 or one ofcomputing devices 170.

FIG. 10 is a timing diagram illustrating score 178 of a plurality ofpatient parameters of a patient over a plurality of time periods. Moreparticularly, FIG. 10 illustrates a trend 250 of the scores of theplurality of periods, each of which in this example is one day. FIG. 10also illustrates the score 178 of patient parameter for the currentperiod (Score_(t)) and the score 178 of patient parameter for theimmediately preceding period (Score_(t-1)).

FIG. 10 also illustrates a window 252 of N preceding periods, which inthis case are the N most recent preceding periods including theimmediately preceding period. N is an integer constant number ofperiods. In the illustrated example, N is 15 days. In an example, N maybe less than 15 days (e.g., 14, 10, less than 7, or other values). In anexample, N may be more than 15 days (e.g., 16, 18, more than 16, orother values). In an example, N may be 3 days. Window 252 may includeconsecutive periods, or may include non-consecutive periods based onexclusion of one or more recent periods as described below with respectto FIGS. 13A and 13B.

In an example, a prediction window may be the period before a predictedVTVF event. For example, the prediction window may be 1 day, such as inFIG. 10. As such, if any score in a 1 day period (e.g., the currentperiod) crosses the threshold from the N preceding periods (e.g., 15 asin FIG. 10), then a prediction will be made. In another example, theprediction window may be less than one day (e.g., 20 hours, less than 20hours, or another value). In an example, the prediction window may bemore than one day (e.g., 2 days, 3 days, 3.5 days, more than 3 days, oranother value). In an example, the prediction window is about 72 hours(e.g., 70 hours to 74 hours). Any value for N may be used with any valuefor the prediction window (e.g., N is 15 days and the prediction windowis 1 day; N is 14 days and the prediction window is 3 days; or any othercombination.

As described above, processing circuitry of a medical device system 8may determine a difference metric based on the difference between thevalues 174 for the current period and the immediately preceding period,e.g., according to equation 1. In some examples, processing circuitry ofa medical device system 8 may determine a difference metric based on thedifference between the values 174 for the current period and theimmediately preceding period, and a representation of the variationvalues 174 for the N preceding periods, e.g., the standard deviation ofthe N preceding values according to equation 2, which may exclude orminimize the effect of baseline variation and/or noise in the differencemetric. Processing circuitry of a medical device system 8 may alsodetermine a threshold 180 based on scores 178 of N preceding periodswithin window 252, e.g., based on a median of the scores within window252, as described above.

FIG. 11 is a tabular representation 260 of an example technique forperiodically determining a score 178 based on respective differencemetrics 176 for each of a plurality of patient parameters. Tabularrepresentation 260 illustrates difference metrics 176 determinedaccording to equation 1 or 2 in the form V_(t,param) _(n) , where trepresents the period and n represents the patient parameter. There are8 different patient parameters for which values 174 are determined inthe illustrated example. Tabular representation 260 also illustratesscores 178 determined based on the sum of squares of the differencemetrics 176, e.g., according to equation 3, in the form of scorer, wheret represents the period.

FIG. 12 is a tabular representation 270 of another example technique forperiodically determining a score 178 based on respective differencemetrics 176 for each of a plurality of patient parameters. The exampletechnique illustrated by representation 270 may be substantially similarto that of representation 260 of FIG. 11. However, according to theexample technique of FIG. 12, processing circuitry of a medical devicesystem 8 may additionally determine whether to include or exclude aparticular patient parameter or difference metric 176 from the score 178based on a patient parameter specific criterion. In some examples,processing circuitry of a medical device system 8 compares each of oneor more of the difference metrics 176 determined for a given period to arespective patient parameter specific criterion, and determines whetherto include the one or more difference metrics 176 in the score 178 basedon the comparison.

The patient parameter specific criterion may discern whether adifference metric 176 for a particular patient parameter, e.g., adirection (positive or negative) or magnitude of the difference metric,indicates a likelihood of an acute cardiac event, or, if included in asum with other difference metrics, would obscure their ability toindicate the likelihood of an acute cardiac event. The comparisons ofdifference metrics 176 to patient parameter specific criteria, andinclusion or exclusion of difference metrics 176 from scores 178, mayoccur on a period-by-period basis, or on a less frequent basis. In someexamples, the processing circuitry or a user may determine that aparticular patient parameter is not relevant for predicting theoccurrence of an acute cardiac event for a given patient or patientpopulation, and exclude the patient parameter permanently or untilincluded by user command. Exclusion of a difference metric 176 for aparticular patient parameter may include assigning a value of 0 to thedifference metric when determining a score 178 for the period, e.g.,according to a sum of squares of difference metrics 176.

Example patient parameter specific criteria include: whether thedifference metric for a percentage of pacing indicates a presence orincrease of pacing during the period; whether the difference metric fora heart rate indicates an increase in heart rate during the period;whether the difference metric for a heart rate variability indicates adecrease in heart rate variability during the period; whether thedifference metric for a patient activity parameter indicates a decreasein patient activity during the period; whether a difference metric for athoracic impedance indicates a fluid index during the period indicatesan increase in the fluid index during the period; whether a differencemetric for a parameter relating to a number, frequency, or duration oftachyarrhythmia events, e.g., NSTs, indicates the occurrence of one ormore tachyarrhythmia events during the period; or whether a differencemetric for a cardiac electrogram morphology parameter indicates changeduring the period. In some examples, processing circuitry may includedifference metrics 176 in the score 178 based on satisfaction of theseexample criteria, e.g., in response to the criteria being satisfied.

FIGS. 13A and 13B are respectively timing diagrams 280 and 290illustrating example techniques for determining a window of N precedingperiods. N is an integer constant number of preceding periods. Timingdiagram 280 of FIG. 13A illustrates a window 252 of the N most recentperiods preceding the current period, e.g., current day in theillustrated example.

Timing diagram 290 of FIG. 13B illustrates an example in which window252 excludes one or more periods 292, such that the N preceding periodsare not consecutive. In some examples, processing circuitry of a medicaldevice system 8 is configured to detect the occurrence of the acutecardiac event, e.g., detect a ventricular tachyarrhythmia using any ofthe techniques described herein, during one of the plurality of periods.In some examples, in response to detecting the acute cardiac event, theprocessing circuitry excludes the period during which the acute cardiacevent was detected from N periods that precede the current period, e.g.,from window 252. In some examples, the processing circuitry additionallyexcludes one or more periods proximate to the period during which theacute cardiac event was detected from N periods, such as one or moreperiods immediately preceding or following the period during which theacute cardiac event was detected. In some examples, 2 to 10 periods,such as 6 periods immediately preceding, one period immediatelyfollowing, and/or the current period, are excluded.

FIG. 14 is a flow diagram illustrating an example technique that may beimplemented by a medical device system 8, e.g., processing circuitry ofthe medical device system, to provide an alert and/or preventativemeasure(s) in response to an acute cardiac event being predicted. Theflowcharts of FIGS. 14-17 are intended to illustrate the functionaloperation of an IMD 10, external device 30, medical system 8, and otherdevices and systems described herein, and should not be construed asreflective of a specific form of software or hardware necessary topractice the methods described. Methods described in conjunction withflow diagrams presented herein may be implemented in a non-transitorycomputer-readable medium that includes instructions for causing aprogrammable processor to carry out the methods described. Anon-transitory computer-readable medium includes but is not limited toany volatile or non-volatile media, such as a RAM, ROM, CD-ROM, NVRAM,EEPROM, flash memory, or other computer-readable media, with the soleexception being a transitory, propagating signal. The instructions maybe implemented by processing circuitry hardware as execution of one ormore software modules, which may be executed by themselves or incombination with other software.

The example methods illustrated by FIGS. 14-17 may be performed, by anyone or more devices described herein, and may be performed, in part, byprocessing circuitry of any one or more devices described herein, suchas by processing circuitry 160 of IMD 10 (which may correspond to any ofICD 10A, ICM 10B, ICD 10C, IPD 10D, or any other IMD), processingcircuitry 200 of external device 30, processing circuitry 228 of server224. For ease of description, the methods of FIGS. 14-16 will bedescribed hereafter as being performed by processing circuitry 160 ofIMD 10.

The example method of FIG. 14 may be performed for each of a pluralityof consecutive periods. According to the example method of FIG. 14,processing circuitry 160 determines patient parameter values 174 foreach of a plurality of patient parameters during the period (300). Thepatient parameters may include any of the patient parameters describedherein, and processing circuitry 160 may determine at least some of thevalues 174 based on physiological signals generated by sensing circuitry162 and/or sensors 166.

Processing circuitry 160 determines a respective difference metric 176for each of the plurality patient parameters for the period (302). Insome examples, processing circuitry 160 determines the respectivedifference metrics 176 based on differences between the current andimmediately preceding values 174 of the patient parameter, e.g., usingequation 1 or 2. Processing circuitry 160 determines a score 178 for theperiod based on the difference metrics 176 for the period, e.g., basedon a sum of the difference metrics (304). In some examples, processingcircuitry 160 determines the score 178 based on a sum of squares of thedifference metrics, e.g., according to equation 3. In some examples,processing circuitry 160 applies a weight to one or more of thedifference metrics when determining the score.

Processing circuitry 160 also determines a threshold 180 for the periodbased on the scores 178 of N preceding periods (306). In some examples,processing circuitry determines the score by applying a coefficient tothe median of the scores 178 for the N preceding periods. Processingcircuitry 160 determines whether the score 178 for the period is greaterthan (or greater than or equal to) the threshold 180 for the period(308). If the score 178 is greater than the threshold 180 (YES of 308),processing circuitry may provide an alert indicating that the acutecardiac event is predicted and/or control delivery of one or morepreventative therapies (310).

Processing circuitry 160 also determines whether the acute cardiac eventwas in fact detected (rather than predicted) during the period (312). Ifthe acute cardiac event is predicted (YES of 312), processing circuitrymay exclude one or more periods, including the current period, from thewindow of N preceding periods using during subsequent periods (314).

FIG. 15 is a flow diagram illustrating an example technique that may beimplemented by a medical device system 8 to determine a score based on aplurality of difference metrics associated with respective patientparameters. The example technique described in FIG. 15 may be used, forexample, by processing circuitry 160 of IMD 10 between blocks 302 and304 of FIG. 14.

According to the example method of FIG. 15, processing circuitry 160determines a difference metric for a particular patient parameter andfor the current period (320). Processing circuitry 160 compares thedifference metric to a patient parameter-specific criterion, e.g., asdescribed above with respect to FIG. 12 (322). Processing circuitry 160determines whether the difference metric 176 for the period satisfiesthe patient parameter-specific criterion (324).

If the criterion is satisfied (YES of 324), processing circuitry 160includes the difference metric 176 in the score 178, e.g., sum ofdifference metrics, for the period (326). If the criterion is notsatisfied (NO of 324), processing circuitry 160 excludes the differencemetric 176 from the score 178 for the period (328). Processing circuitry160 determines whether there are additional difference metrics 176 foradditional patient parameters to which parameter-specific criteria areto be applied during the period (330).

FIG. 16 is a flow diagram illustrating an example technique that may beimplemented by a medical device system 8, clinician, or other user, toselect one or more preventative measure(s) for delivery in response toan acute cardiac event being predicted. For ease of description, theexample of FIG. 16 is described as being performed by processingcircuitry 160 of IMD 10.

According to the example method of FIG. 16, processing circuitry 160determines that the score 178 for the current period exceeds thethreshold 180 for the period (340, e.g., YES of 308 of FIG. 14).Processing circuitry 160 determines which one or more patient parametersexhibited the greatest, or most significant, change during the period(342). For example, processing circuitry 160 may identify the one ormore difference metrics 176 for the current having the greatest absolutevalue, or the greatest absolute value relative to a mean, median, orstandard deviation of difference metrics for the parameter during the Npreceding periods, e.g., determined as a percentage, ratio, or othernormalized value.

Processing circuitry 160 selects one or more preventative measures,e.g., therapies configured to prevent the acute cardiac event,associated with the one or more identified patient parameters (344). Insome examples, IMD 10 may be configured to deliver, and/or control oneor more other devices to deliver, a plurality of different therapiesconfigured to prevent the acute cardiac event. Different therapies mayinclude different cardiac pacing algorithms, different types of,targets, and/or programs for neuromodulation, and delivery of differentdrugs, delivery of one or more drugs to different targets, and ordelivery of one or more drugs according to different drug deliveryregimens.

Memory 170 may store information associating one or more preventativetherapies with one or more patient parameters, and processing circuitry160 may select one or more preventative therapies according to theinformation stored in memory 170. The associations of therapies andpatient parameters may be programmed by a clinician and/or determinedbased on an analysis of historical efficacy of a particular therapy inpreventing an acute cardiac event, for patient 14 and/or a population ofpatients anatomically, physiologically, and or clinically similar topatient 14. Processing circuitry 160 controls IMD 10 or another medicaldevice to deliver the selected preventative measure(s) (346). Forexample, if processing circuitry 160 determines that a patient parameter174 associated with heart rate is consistently too fast at the time apatient parameter 174 associated with patient activity indicates noincrease in physical activity, a vagal stimulation can be triggered toslow down the heart rate or down-driving pacing can be triggered. On theother hand, if processing circuitry 160 determines that a patientparameter 174 associated with heart rate is slow in combination with anoccurrence of more PVCs, then overdrive pacing can be triggered.

FIG. 17 is a flow diagram illustrating an example technique that may beimplemented by a medical device system to determine and/or modify a setof patient parameters or weightings applied to patient parameters usedto determine whether an acute cardiac event is predicted. For ease ofdescription, the example of FIG. 17 is described as being performed byprocessing circuitry 160 of IMD 10.

According to the example method of FIG. 17, processing circuitry 160detects an acute cardiac event, e.g., ventricular tachyarrhythmia,during a period (350). Processing circuitry 160 determines the amountand/or significance of change exhibited during the period for theplurality of patient parameters (352). For example, processing circuitry160 may identify the absolute values of difference metrics, or theabsolute values relative to a mean, median, or standard deviation ofdifference metrics for the parameter during the N preceding periods. Inthis manner, processing circuitry 160 may determine the relativesignificance or importance of the various patient parameters inpredicting the detected cardiac event. Based on the relativesignificance or importance of the patient parameters, processingcircuitry 160 may include or exclude certain patient parameters from usein the techniques to predict the acute cardiac event, or modify patientparameter-specific weighting parameters applied to the differencemetrics to determine a score (e.g., sum-based) for a period, which mayemphasize or de-emphasize the importance of certain patient parameters(354).

FIGS. 18-22 are tables (360, 370, 380, 390, and 400, respectively) ofexperimental results illustrating the performance of the exampletechniques of this disclosure in predicting ventricular tachyarrhythmia.In FIGS. 18-20, each row may correspond to a different device (e.g., adifferent device serial number). In FIGS. 21 and 22, each row maycorrespond to a different patient identification number. In general,each row may correspond to a different patient. Twenty-fiveICD-indicated patients were prospectively enrolled. After ICDimplantation, each patient underwent weekly data collections forsix-month follow-up and appropriate VTVF events were determined. A VTVFevent could be a single discrete VT or VF episode or a VTVF storm withinter-episode interval less than 24 hours. An algorithm was developed tocreate a weighted score based on the assessment of directional changesin values of multiple device-derived (e.g., Cardiac Compass®) patientparameters over a 15-day moving window. The algorithm was thenretrospectively tested to compare the weighted score one day before anevent vs. the weighted score over 15-day window. The efficiency of theprediction in one day before a VTVF event was determined with thesensitivity and the specificity.

The patients enrolled in this study had LVEF 44.5±15.2% and NYHA class1.3±0.6. In the enrolled 25 patients, 11 (44%) had coronary heartdisease, 14 (56%) had cardiomyopathy, 7 (28%) had hypertension, and 20(80%) had a history of sustained VT or VF. Of 25 patients, 10 patients(40%) developed a total of 123 appropriate VTVF episodes (12.4±13.2,median 5 per patient) that were terminated by ICD therapies. Of these123 episodes, 100 were classified as VT while remaining 23 episodes wereVF. When the weighted-score algorithm was tested in all 25 patients, theprediction of VTVF events one day before the occurrence had a 100%sensitivity and 74% specificity.

The experimental results, e.g., as illustrated in FIGS. 17-19,demonstrate that VTVF events can be predicted one day in advanceaccording to the techniques of this disclosure, which may provide a timewindow for executing appropriate measures to prevent VTVF occurrence,especially for VTVF storms.

FIG. 23 is a table 380 illustrating a receiver operator characteristicfor a coefficient used to determine a threshold 180 for determiningwhether an acute cardiac event is predicted according to the exampletechniques of this disclosure. As described in greater detail above,processing circuitry 160 may determine threshold 180 for the currentperiod by applying a coefficient to a median of scores 178 for Npreceding periods. The value of the coefficient may be determined and/ormodified, based on a receiver operator characteristic for thecoefficient relative to the sensitivity and specificity of acute cardiacevent prediction according the techniques of this disclosure usingdifferent values of the coefficient. The data for determining thereceiver operator characteristic may be historical data from thepatient, or a population of similar patients and/or experimentalsubjects.

FIG. 24 is a conceptual diagram 420 illustrating patient parameters,e.g., physiological and pathophysiological parameters, that maycontribute to the occurrence of an acute cardiac event. In general, thetechniques of this disclosure enable prediction of an acute cardiacevent based on a combined score from a plurality of patient parameters,which may include clinical parameters and/or parameters derived from amedical device. Changes in the parameters may reflect changes in apatient's electrophysiological substrate and/or anatomical milieu thatprecede an acute cardiac event.

The techniques described herein may use a moving window computation forall possible risk variables. The techniques described herein may includecalculating a weighted score for prediction of imminent VTVF events.Such a calculation, and other techniques, are based on the findings thatrisk factors change in a temporal manner and, generally, there may notbe a single variable that can consistently be used predict VTVF eventsin the same patient or the population. The possible risk variables forconsideration in the present techniques may include: (1) pathologicalsubstrates (e.g., cardiac diseases, myocardial infarction, etc.), (2)daily monitoring parameters (e.g., autonomic signature, thoracicimpedance, ventricular pacing, etc.), such as included in CardiacCompass®, (3) daily non-VTVF arrhythmic burden (e.g., NSVT, ATAF, PVCburden, etc.), and (4) cardiac electrogram alternations (such as T-wavealternans, repolarization alternations, QRS duration and fragmentation,etc.). Further illustration of the possible risk variables may be seenin FIG. 24.

Patient parameters relating to arrhythmic substrate may include orindicate the presence or extent of: coronary artery disease (CAD), suchas scar and vulnerable plaque; hypertensive heart disease;cardiomyopathy; channelopathies, with may be reflected in long QTsyndrome (LQTS) or Brugada syndrome; other genetic predisposition toacute cardiac events, such as single nucleotide polymorphism; heartfailure, including dilatation and/or fibrosis; the presence and/orextent of sustained VT, AT, and/or AF; patient lifestyle andcomorbidities. Patient parameters relating to physiological triggers foracute cardiac events may include or indicate the presence or extent of:autonomic changes, such as increase sympathetic and/or decreasedparasympathetic drive; acute ischemia; physical exertion; hypoxia; drugeffects; electrolyte abnormalities; myocardial toxin; heart failure,which may be autonomic, metabolic, due to supraventricular tachycardia(SVT), and/or cardiogenic shock; or the presence of other arrhythmias,such as PVCs, R-on-T events, non-sustained ventricular tachycardias,short-long-short rhythm, or the like. The occurrence of one or moretriggers in the presence of one or more indicators of arrhythmicsubstrate may lead to electrical instability, as illustrated in FIG. 24,and consequently be particularly predictive of the occurrence of anacute cardiac event. For example, as illustrated in FIG. 24, theoccurrence of one or more triggers in the presence of one or moreindicators of arrhythmic substrate may lead to increase ADP/ARPdispersion, decrease conduction velocity, increase automaticity, and/orincreased triggered activities. The illustration of FIG. 24 may beconsidered a matrix of possible patient parameters that can be monitoredin combination to predict an acute cardiac event, such as ventriculartachyarrhythmia.

Any of the above patient parameters, or any patient parameters relatedto these conditions, may be used to predict acute cardiac eventsaccording to the techniques of this disclosure. These parameters may bedetected by processing circuitry 160 based on device-derivedphysiological parameters and/or indications from a clinician, e.g., viaan external device 30 or other computing device. For example, changes inheart rate, heart rate variability, and the occurrence of PVCs mayindicate changes in sympathetic/parasympathetic drive.

A sudden oscillation in any of the patient parameters described hereinmay be considered a risk of an acute cardiac event. A sum ofoscillations of several parameters may be considered as a combined riskscore with the largest oscillation contributing to the combined scorethe most. This concept may provide weighted score or contributor. Thetechniques described herein, e.g., including determining a score for aperiod based on a sum of difference metrics for a plurality of patientparameters and comparing the score to a longer term mean or median ofthe scores, may indicate the sum of the oscillations and allowidentification of the most significant patient parameters thatcontribute to the occurrence cardiac events for a particular patient.

The patient parameters used to predict acute cardiac events for aparticular patient may be pre-defined (such as use only T-wave alternansand/or the frequency of non-sustained ventricular tachycardia). In someexamples, many patient parameters are monitored to predict acute cardiacevents and any (or some) of the parameters that show undesired changeswill be weighted in the prediction score. The parameters that showsignificant oscillations prior to an acute cardiac event may vary frompatient-to-patient, or from event-to-event for a particular patient. Forexample, one event may be predicted based on significant oscillations inT-wave alternans and the frequency of non-sustained ventriculartachycardia, while another is predicted based on significantoscillations in T-wave alternans and heart rate variability. In thismanner, the prediction may be tailored to a particular patient, e.g.,individual-based prediction.

As described herein, the techniques of this disclosure also allowprocessing circuitry 160 to determine the most important patientparameter(s) that contributed to the supra-threshold score and,consequently, one or more likely causes of the cardiac event. Asdescribed herein, this may be useful for determining and/or adjustingover time a set of parameters and/or weightings used to determine scoresand predict cardiac events for a particular patient. In addition, asdescribed herein, one or more preventative measures may be selectedbased on the identified significant parameters and most likely causes ofthe event. The targeted measures selected to prevent the cardiac eventin this manner may be referred to as predictor-guided preventativemeasure(s).

The associations of patient-parameters and targeted preventativemeasures may be configured based on known or determined relationshipsbetween patient parameters for causing cardiac events. For example, ifan event occurrence needs the co-existence of parameters A and B or Aand C, parameter A is the most important contributor, and a preventativemeasure configured to reduce or counteract the oscillation in parameterA could be delivered. Of course, preventive measure targeted toparameters B or C could additionally or alternatively be delivered.

In an example, if the major score contributor is a reduction in HRV(e.g., which may be an indication of sympathetic surge), then vagalstimulation (e.g., using neuromodulation) may be initiated. For example,if T-wave alternans change increases, a pacing algorithm may betriggered to reduce T-wave alternans. Other methods may include drugperfusion, termination of a physical activity, or other techniques, suchas may be based on the rick contributor analysis in the calculatedweighted score.

Various aspects of the techniques may be implemented within one or moreprocessors, including one or more microprocessors, DSPs, ASICs, FPGAs,or any other equivalent integrated or discrete logic circuitry, as wellas any combinations of such components, embodied in programmers, such asphysician or patient programmers, electrical stimulators, or otherdevices. The term “processor” or “processing circuitry” may generallyrefer to any of the foregoing logic circuitry, alone or in combinationwith other logic circuitry, or any other equivalent circuitry.

In one or more examples, the functions described in this disclosure maybe implemented in hardware, software, firmware, or any combinationthereof. If implemented in software, the functions may be stored on, asone or more instructions or code, a computer-readable medium andexecuted by a hardware-based processing unit. Computer-readable mediamay include computer-readable storage media forming a tangible,non-transitory medium. Instructions may be executed by one or moreprocessors, such as one or more DSPs, ASICs, FPGAs, general purposemicroprocessors, or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used herein may referto one or more of any of the foregoing structure or any other structuresuitable for implementation of the techniques described herein.

In addition, in some aspects, the functionality described herein may beprovided within dedicated hardware and/or software modules. Depiction ofdifferent features as modules or units is intended to highlightdifferent functional aspects and does not necessarily imply that suchmodules or units must be realized by separate hardware or softwarecomponents. Rather, functionality associated with one or more modules orunits may be performed by separate hardware or software components, orintegrated within common or separate hardware or software components.Also, the techniques could be fully implemented in one or more circuitsor logic elements. The techniques of this disclosure may be implementedin a wide variety of devices or apparatuses, including an IMD, anexternal programmer, a combination of an IMD and external programmer, anintegrated circuit (IC) or a set of ICs, and/or discrete electricalcircuitry, residing in an IMD and/or external programmer.

In an example, a medical device system may comprise means for performingany of the methods or techniques described herein.

In an example, a non-transitory computer-readable storage medium maycomprise instructions, that when executed by processing circuitry of amedical device system, cause the medical device system to perform any ofthe methods or techniques described herein.

The following numbered clauses demonstrate one or more aspects of thisdisclosure.

Clause 1: In one example, a medical device system comprises sensingcircuitry configured to generate one or more physiological signals of apatient; and processing circuitry that, for each of a plurality ofperiods, is configured to: determine a respective value for each of aplurality of patient parameters, wherein, for one or more of theplurality of patient parameters, the respective values are determinedbased on the one or more physiological signals generated during theperiod; for each of the plurality of patient parameters, determine adifference metric for a current period for each of the plurality ofperiods based on a value of the patient parameter determined for thecurrent period and a value of the patient parameter determined for animmediately preceding period of the plurality periods; determine a scorefor the current period based on a sum of the difference metrics for thecurrent period for the one or more of the plurality of patientparameters; determine a threshold for the current period based on scoresdetermined for N periods of the plurality of periods that precede thecurrent period, wherein N is an integer constant; compare the score forthe current period to the threshold for the current period; anddetermine whether to generate an alert indicating that an acute cardiacevent of the patient is predicted based on the comparison.

Clause 2: In some examples of the system of clause 1, the processingcircuitry is configured to determine a difference between the value ofthe patient parameter determined for the current period and the value ofthe patient parameter determined for the immediately preceding period asthe difference metric for the current period.

Clause 3: In some examples of the system of clause 1 or 2, theprocessing circuitry is configured to determine the difference metricfor the current period as a ratio between: a difference between thevalue of the patient parameter determined for the current period and thevalue of the patient parameter determined for the immediately precedingperiod; and a measure of variation of values of the patient parameterdetermined for the N periods of the plurality of periods that precedethe current period.

Clause 4: In some examples of the system of clause 3, the measure ofvariation comprises a standard deviation of the values of the patientparameter determined for the N periods of the plurality of periods thatprecede the current period.

Clause 5: In some examples of the system of any of clauses 1-4, theprocessing circuitry is configured to determine the score for thecurrent period at least by determining a sum of squares of thedifference metrics for the current.

Clause 6: In some examples of the system of any of clauses 1-5, theprocessing circuitry is configured to determine the threshold based on amedian of the scores determined for the N periods preceding the currentperiod.

Clause 7: In some examples of the system of any of clauses 1-6, theprocessing circuitry is configured to: compare one or more of thedifference metrics for the current period to a patient parameterspecific criterion; and determine whether to include the one or more ofthe difference metrics in the sum based on the comparison.

Clause 8: In some examples of the system of any of clauses 1-7, thealert indicates that a ventricular tachyarrhythmia is predicted.

Clause 9: In some examples of the system of any of clauses 1-8, theprocessing circuitry is configured to: detect the acute cardiac eventduring one of the plurality of periods; and exclude the period duringwhich the acute cardiac event was detected from N periods that precedethe current period.

Clause 10: In some examples of the system of any of clauses 1-9, thesystem further comprises therapy delivery circuitry configured todeliver a therapy to the patient to prevent the predicted acute cardiacevent, wherein the processing circuitry is configured to determinewhether to control the therapy delivery circuitry to deliver the therapybased on the comparison of the score for the current period to thethreshold for the current period.

Clause 11: In some examples of the system of clause 10, the therapydelivery circuitry is configured to deliver a plurality of therapies tothe patient to prevent the predicted acute cardiac event, and whereinthe processing circuitry is configured to: for each of the plurality ofpatient parameters, compare the difference metric determined for thecurrent period to difference metrics determined for the N periodspreceding the current period; identify one of the plurality of patientparameters having a most significant change in the difference metricfrom the N periods to the current period; select one of the plurality oftherapies associated with the identified one of the plurality of patientparameters; and control the therapy delivery circuitry to deliver theselected one of the plurality of therapies.

Clause 12: In some examples of the system of any of clauses 1-11, thesystem further comprises an implantable medical device that comprisesthe sensing circuitry and the processing circuitry.

Clause 13: In some examples of the system of clause 12, the implantablemedical device comprises an implantable cardioverter defibrillatorfurther comprising therapy delivery circuitry configured to deliveranti-tachyarrhythmia shocks.

Clause 14: In some examples of the system of clause 12 or 13, theimplantable medical device comprises a leadless monitor comprising ahousing configured for subcutaneous implantation that houses the sensingcircuitry and the processing circuitry, wherein the housing includes aplurality of electrodes coupled to the sensing circuitry, and whereinthe sensing circuitry is configured to generate a subcutaneous cardiacelectrogram based on cardiac signals sensed via the electrodes.

Clause 15: In some examples of the system of any of clauses 1-14, theprocessing circuitry is further configured to: identify one or more ofthe plurality of patient parameters that contributed to the score beinggreater than the threshold, wherein the processing circuitry identifiesthe one or more of the plurality of patient parameters having mostsignificant changes in the difference metric from the N periods to thecurrent period as the one or more of the plurality of patient parametersthat contributed to the score being greater than the threshold; and toat least one of: exclude a patient parameter from the score for asubsequent period, include a patient parameter for a subsequent period,or modify one or more weights applied to one or more of the differencemetrics when determining the score based on the identified one or morepatient parameters.

Clause 16: In some examples of the system of clause 15, the processingcircuitry is configured to select one or more preventative measures todeliver to the patient based on the one or more identified patientparameters that contributed to the score being greater than thethreshold.

Clause 17: In some examples, a method comprises generating, by sensingcircuitry of a medical device system, one or more physiological signalsof a patient; and for each of a plurality of periods, by processingcircuitry of the medical device system: determining a respective valuefor each of a plurality of patient parameters, wherein, for one or moreof the plurality of patient parameters, the respective values aredetermined based on the one or more physiological signals generatedduring the period; for each of the plurality of patient parameters,determining a difference metric for a current period for each of theplurality of periods based on a value of the patient parameterdetermined for the current period and a value of the patient parameterdetermined for an immediately preceding period of the plurality periods;determining a score for the current period based on a sum of thedifference metrics for the current period for the one or more of theplurality of patient parameters; determining a threshold for the currentperiod based on scores determined for N periods of the plurality ofperiods that precede the current period, wherein N is an integerconstant; comparing the score for the current period to the thresholdfor the current period; and determining whether to generate an alertindicating that an acute cardiac event of the patient is predicted basedon the comparison.

Clause 18: In some examples of the method of clause 17, determining thedifference metric for the current period comprises determining adifference between the value of the patient parameter determined for thecurrent period and the value of the patient parameter determined for theimmediately preceding period.

Clause 19: In some examples of the method clause 17 or 18, determiningthe difference metric for the current period comprises determining aratio between: a difference between the value of the patient parameterdetermined for the current period and the value of the patient parameterdetermined for the immediately preceding period; and a measure ofvariation of values of the patient parameter determined for the Nperiods of the plurality of periods that precede the current period.

Clause 20: In some examples of the method of clause 20: the measure ofvariation comprises a standard deviation of the values of the patientparameter determined for the N periods of the plurality of periods thatprecede the current period.

Clause 21: In some examples of the method of any of clauses 17-20,determining the score for the current period comprises determining a sumof squares of the difference metrics for the current period.

Clause 22: In some examples of the method of any of clauses 17-21,determining the threshold for the current period comprises determining amedian of the scores determined for the N periods preceding the currentperiod.

Clause 23: In some examples of the method of any of clauses 17-22, themethod further comprises, by the processing circuitry: comparing one ormore of the difference metrics for the current period to a patientparameter specific criterion; and determining whether to include the oneor more of the difference metrics in the sum based on the comparison.

Clause 24: In some examples of the method of any of clauses 17-23, thealert indicates that a ventricular tachyarrhythmia is predicted.

Clause 25: In some examples of the method of any of clauses 17-24, themethod further comprises, by the processing circuitry: detecting theacute cardiac event during one of the plurality of periods; andexcluding the period during which the acute cardiac event was detectedfrom N periods that precede the current period.

Clause 26: In some examples of the method of any of clauses 17-25, themethod further comprises, by the processing circuitry of the medicaldevice system, determining whether to control therapy delivery circuitryof the medical device system to deliver a therapy to the patient toprevent the predicted acute cardiac event based on the comparison of thescore for the current period to the threshold for the current period.

Clause 27: In some examples of the method of clause 26, the therapydelivery circuitry is configured to deliver a plurality of therapies tothe patient to prevent the predicted acute cardiac event, the methodfurther comprising, by the processing circuitry: for each of theplurality of patient parameters, comparing the difference metricdetermined for the current period to difference metrics determined forthe N periods preceding the current period; identifying one of theplurality of patient parameters having a most significant change in thedifference metric from the N periods to the current period; selectingone of the plurality of therapies associated with the identified one ofthe plurality of patient parameters; and controlling the therapydelivery circuitry to deliver the selected one of the plurality oftherapies.

Clause 28: In some examples of the method of any of clauses 17-27, themethod further comprises identifying one or more of the plurality ofpatient parameters that contributed to the score being greater than thethreshold; identifying the one or more of the plurality of patientparameters that contributed to the score being greater than thethreshold comprises identifying one or more of the plurality of patientparameters having most significant changes in the difference metric fromthe N periods to the current period; and at least one of: excluding apatient parameter from the score for a subsequent period, including apatient parameter for a subsequent period, or modifying one or moreweights applied to one or more of the difference metrics whendetermining the score based on the identified one or more patientparameters.

Clause 29: In some examples of the method of clause 28, the methodfurther comprises selecting one or more preventative measures to deliverto the patient based on the one or more identified patient parametersthat contributed to the score being greater than the threshold.

Clause 30: In some examples, a medical device system comprises: meansfor generating one or more physiological signals of a patient; and foreach of a plurality of periods: means for determining a respective valuefor each of a plurality of patient parameters, wherein, for one or moreof the plurality of patient parameters, the respective values aredetermined based on the one or more physiological signals generatedduring the period; for each of the plurality of patient parameters,means for determining a difference metric for a current period for eachof the plurality of periods based on a value of the patient parameterdetermined for the current period and a value of the patient parameterdetermined for an immediately preceding period of the plurality periods;means for determining a score for the current period based on a sum ofthe difference metrics for the current period for the one or more of theplurality of patient parameters; means for determining a threshold forthe current period based on scores determined for N periods of theplurality of periods that precede the current period, wherein N is aninteger constant; means for comparing the score for the current periodto the threshold for the current period; and means for determiningwhether to generate an alert indicating that an acute cardiac event ofthe patient is predicted based on the comparison.

Clause 31: In some examples, a non-transitory computer-readable storagemedium comprises instructions, that when executed by processingcircuitry of a medical device system, cause the medical device systemto: receive one or more physiological signals of a patient; and for eachof a plurality of periods: determine a respective value for each of aplurality of patient parameters, wherein, for one or more of theplurality of patient parameters, the respective values are determinedbased on the one or more physiological signals generated during theperiod; for each of the plurality of patient parameters, determine adifference metric for a current period for each of the plurality ofperiods based on a value of the patient parameter determined for thecurrent period and a value of the patient parameter determined for animmediately preceding period of the plurality periods; determine a scorefor the current period based on a sum of the difference metrics for thecurrent period for the one or more of the plurality of patientparameters; determine a threshold for the current period based on scoresdetermined for N periods of the plurality of periods that precede thecurrent period, wherein N is an integer constant; compare the score forthe current period to the threshold for the current period; anddetermine whether to generate an alert indicating that an acute cardiacevent of the patient is predicted based on the comparison.

Various aspects of the disclosure have been described. These and otheraspects are within the scope of the following claims.

What is claimed is:
 1. A medical device system comprising: sensing circuitry configured to generate one or more physiological signals of a patient; and processing circuitry that, for each of a plurality of periods, is configured to: determine a respective value for each of a plurality of patient parameters, wherein, for one or more of the plurality of patient parameters, the respective values are determined based on the one or more physiological signals generated during the period; for each of the plurality of patient parameters, determine a difference metric for a current period for each of the plurality of periods based on a value of the patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period of the plurality periods; determine a score for the current period based on a sum of the difference metrics for the current period for the one or more of the plurality of patient parameters; determine a threshold for the current period based on scores determined for N periods of the plurality of periods that precede the current period, wherein N is an integer constant; compare the score for the current period to the threshold for the current period; and determine whether to generate an alert indicating that an acute cardiac event of the patient is predicted based on the comparison.
 2. The system of claim 1, wherein the processing circuitry is configured to determine a difference between the value of the patient parameter determined for the current period and the value of the patient parameter determined for the immediately preceding period as the difference metric for the current period.
 3. The system of claim 1, wherein the processing circuitry is configured to determine the difference metric for the current period as a ratio between: a difference between the value of the patient parameter determined for the current period and the value of the patient parameter determined for the immediately preceding period; and a measure of variation of values of the patient parameter determined for the N periods of the plurality of periods that precede the current period.
 4. The system of claim 3, wherein the measure of variation comprises a standard deviation of the values of the patient parameter determined for the N periods of the plurality of periods that precede the current period.
 5. The system of claim 1, wherein the processing circuitry is configured to determine the score for the current period at least by determining a sum of squares of the difference metrics for the current period.
 6. The system of claim 1, wherein the processing circuitry is configured to determine the threshold based on a median of the scores determined for the N periods preceding the current period.
 7. The system of claim 1, wherein the processing circuitry is configured to: compare one or more of the difference metrics for the current period to a patient parameter specific criterion; and determine whether to include the one or more of the difference metrics in the sum based on the comparison.
 8. The system of claim 1, wherein the alert indicates that a ventricular tachyarrhythmia is predicted.
 9. The system of claim 1, wherein the processing circuitry is configured to: detect the acute cardiac event during one of the plurality of periods; and exclude the period during which the acute cardiac event was detected from N periods that precede the current period.
 10. The system of claim 1, further comprising therapy delivery circuitry configured to deliver a therapy to the patient to prevent the predicted acute cardiac event, wherein the processing circuitry is configured to determine whether to control the therapy delivery circuitry to deliver the therapy based on the comparison of the score for the current period to the threshold for the current period.
 11. The system of claim 10, wherein the therapy delivery circuitry is configured to deliver a plurality of therapies to the patient to prevent the predicted acute cardiac event, and wherein the processing circuitry is configured to: for each of the plurality of patient parameters, compare the difference metric determined for the current period to difference metrics determined for the N periods preceding the current period; identify one of the plurality of patient parameters having a most significant change in the difference metric from the N periods to the current period; select one of the plurality of therapies associated with the identified one of the plurality of patient parameters; and control the therapy delivery circuitry to deliver the selected one of the plurality of therapies.
 12. The system of claim 1, further comprising an implantable medical device that comprises the sensing circuitry and the processing circuitry.
 13. The system of claim 12, wherein the implantable medical device comprises an implantable cardioverter defibrillator further comprising therapy delivery circuitry configured to deliver anti-tachyarrhythmia shocks.
 14. The system of claim 12, wherein the implantable medical device comprises a leadless monitor comprising a housing configured for subcutaneous implantation that houses the sensing circuitry and the processing circuitry, wherein the housing includes a plurality of electrodes coupled to the sensing circuitry, and wherein the sensing circuitry is configured to generate a subcutaneous cardiac electrogram based on cardiac signals sensed via the electrodes.
 15. The system of claim 1, wherein the processing circuitry is further configured to: identify one or more of the plurality of patient parameters that contributed to the score being greater than the threshold, wherein the processing circuitry identifies the one or more of the plurality of patient parameters having most significant changes in the difference metric from the N periods to the current period as the one or more of the plurality of patient parameters that contributed to the score being greater than the threshold; and to at least one of: exclude a patient parameter from the score for a subsequent period, include a patient parameter for a subsequent period, or modify one or more weights applied to one or more of the difference metrics when determining the score based on the identified one or more patient parameters.
 16. The system of claim 15, wherein the processing circuitry is configured to select one or more preventative measures to deliver to the patient based on the one or more identified patient parameters that contributed to the score being greater than the threshold.
 17. A method comprising: generating, by sensing circuitry of a medical device system, one or more physiological signals of a patient; and for each of a plurality of periods, by processing circuitry of the medical device system: determining a respective value for each of a plurality of patient parameters, wherein, for one or more of the plurality of patient parameters, the respective values are determined based on the one or more physiological signals generated during the period; for each of the plurality of patient parameters, determining a difference metric for a current period for each of the plurality of periods based on a value of the patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period of the plurality periods; determining a score for the current period based on a sum of the difference metrics for the current period for the one or more of the plurality of patient parameters; determining a threshold for the current period based on scores determined for N periods of the plurality of periods that precede the current period, wherein N is an integer constant; comparing the score for the current period to the threshold for the current period; and determining whether to generate an alert indicating that an acute cardiac event of the patient is predicted based on the comparison.
 18. The method of claim 17, wherein determining the difference metric for the current period comprises determining a difference between the value of the patient parameter determined for the current period and the value of the patient parameter determined for the immediately preceding period.
 19. The method of claim 17, wherein determining the difference metric for the current period comprises determining a ratio between: a difference between the value of the patient parameter determined for the current period and the value of the patient parameter determined for the immediately preceding period; and a measure of variation of values of the patient parameter determined for the N periods of the plurality of periods that precede the current period.
 20. The method of claim 19, wherein the measure of variation comprises a standard deviation of the values of the patient parameter determined for the N periods of the plurality of periods that precede the current period.
 21. The method of claim 17, wherein determining the score for the current period comprises determining a sum of squares of the difference metrics for the current period.
 22. The method of claim 17, wherein determining the threshold for the current period comprises determining a median of the scores determined for the N periods preceding the current period.
 23. The method of claim 17, further comprising, by the processing circuitry: comparing one or more of the difference metrics for the current period to a patient parameter specific criterion; and determining whether to include the one or more of the difference metrics in the sum based on the comparison.
 24. The method of claim 17, wherein the alert indicates that a ventricular tachyarrhythmia is predicted.
 25. The method of claim 17, further comprising, by the processing circuitry: detecting the acute cardiac event during one of the plurality of periods; and excluding the period during which the acute cardiac event was detected from N periods that precede the current period.
 26. The method of claim 17, further comprising, by the processing circuitry of the medical device system, determining whether to control therapy delivery circuitry of the medical device system to deliver a therapy to the patient to prevent the predicted acute cardiac event based on the comparison of the score for the current period to the threshold for the current period.
 27. The method of claim 26, wherein the therapy delivery circuitry is configured to deliver a plurality of therapies to the patient to prevent the predicted acute cardiac event, the method further comprising, by the processing circuitry: for each of the plurality of patient parameters, comparing the difference metric determined for the current period to difference metrics determined for the N periods preceding the current period; identifying one of the plurality of patient parameters having a most significant change in the difference metric from the N periods to the current period; selecting one of the plurality of therapies associated with the identified one of the plurality of patient parameters; and controlling the therapy delivery circuitry to deliver the selected one of the plurality of therapies.
 28. The method of claim 17, further comprising: identifying one or more of the plurality of patient parameters that contributed to the score being greater than the threshold; identifying the one or more of the plurality of patient parameters that contributed to the score being greater than the threshold comprises identifying one or more of the plurality of patient parameters having most significant changes in the difference metric from the N periods to the current period; and at least one of: excluding a patient parameter from the score for a subsequent period, including a patient parameter for a subsequent period, or modifying one or more weights applied to one or more of the difference metrics when determining the score based on the identified one or more patient parameters.
 29. The method of claim 28, further comprising selecting one or more preventative measures to deliver to the patient based on the one or more identified patient parameters that contributed to the score being greater than the threshold.
 30. A medical device system comprising: means for generating one or more physiological signals of a patient; and for each of a plurality of periods: means for determining a respective value for each of a plurality of patient parameters, wherein, for one or more of the plurality of patient parameters, the respective values are determined based on the one or more physiological signals generated during the period; for each of the plurality of patient parameters, means for determining a difference metric for a current period for each of the plurality of periods based on a value of the patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period of the plurality periods; means for determining a score for the current period based on a sum of the difference metrics for the current period for the one or more of the plurality of patient parameters; means for determining a threshold for the current period based on scores determined for N periods of the plurality of periods that precede the current period, wherein N is an integer constant; means for comparing the score for the current period to the threshold for the current period; and means for determining whether to generate an alert indicating that an acute cardiac event of the patient is predicted based on the comparison.
 31. A non-transitory computer-readable storage medium comprising instructions, that when executed by processing circuitry of a medical device system, cause the medical device system to: receive one or more physiological signals of a patient; and for each of a plurality of periods: determine a respective value for each of a plurality of patient parameters, wherein, for one or more of the plurality of patient parameters, the respective values are determined based on the one or more physiological signals generated during the period; for each of the plurality of patient parameters, determine a difference metric for a current period for each of the plurality of periods based on a value of the patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period of the plurality periods; determine a score for the current period based on a sum of the difference metrics for the current period for the one or more of the plurality of patient parameters; determine a threshold for the current period based on scores determined for N periods of the plurality of periods that precede the current period, wherein N is an integer constant; compare the score for the current period to the threshold for the current period; and determine whether to generate an alert indicating that an acute cardiac event of the patient is predicted based on the comparison. 